\documentclass[12pt,letterpaper]{article} \pdfminorversion=6 \usepackage[top=1.0in, bottom=1in, left=1in, right=1in]{geometry} \usepackage{amssymb} \usepackage{amsmath} \usepackage{graphicx} \usepackage{setspace} \usepackage{rotating} \usepackage{booktabs} \usepackage{longtable} \usepackage[colorlinks,citecolor=black,linkcolor=black,urlcolor=blue]{hyperref} \usepackage{xcolor} \usepackage[final]{pdfpages} \usepackage[normalem]{ulem} \usepackage{threeparttable} \usepackage[T1]{fontenc} \usepackage[utf8]{inputenc} \usepackage[active]{srcltx} \usepackage{amstext} \usepackage{natbib} \usepackage{lscape} \usepackage[titletoc]{appendix} \usepackage[justification=centering]{caption} \usepackage{soul} \newcommand{\comment}[1]{} \interfootnotelinepenalty=10000 \tolerance=20000 \begin{document} \thispagestyle{empty} { % set font to helvetica (arial) to make it 508-compliant \fontfamily{phv}\selectfont \begin{center} {\LARGE \textbf{The International Trade and Production}} \\ \vspace{0.25in} {\LARGE \textbf{Database for Estimation - Release 2}} \\ \vspace{0.25in} {\LARGE \textbf{(ITPD-E-R02)}} \\ \vspace{1in} {\Large Ingo Borchert} \\\vspace{.25in} {\Large Mario Larch} \\\vspace{.25in} {\Large Serge Shikher} \\\vspace{.25in} {\Large Yoto V. Yotov} \vspace{1in} {\large ECONOMICS WORKING PAPER SERIES}\\ Working Paper 2022--07--A \\ \vspace{0.5in} U.S. INTERNATIONAL TRADE COMMISSION \\ 500 E Street SW \\ Washington, DC 20436 \\ \vspace{0.5in} July 2022 \\ \end{center} \vfill %\noindent Optional: Acknowledgements, thanks, etc.\\ \vspace{1em} \noindent Office of Economics working papers are the result of ongoing professional research of USITC Staff and are solely meant to represent the opinions and professional research of individual authors. These papers are not meant to represent in any way the views of the U.S.\ International Trade Commission or any of its individual Commissioners. \newpage \thispagestyle{empty} % remove headers, footers, and page numbers from cover page \begin{flushleft} The International Trade and Production Database for Estimation - Release 2 (ITPD-E-R02) \\ Ingo Borchert, Mario Larch, Serge Shikher, and Yoto V. Yotov \\ Economics Working Paper 2022--07--A\\ July 2022 \\~\\ \end{flushleft} \vfill \begin{abstract} \noindent This paper introduces Release 2 of the International Trade and Production Database for Estimation (ITPD-E-R02). ITPD-E-R02 covers the period 1986-2019 for 265 countries and 170 industries across four broad sectors: Agriculture, Mining and Energy, Manufacturing, and Services. Some of the improvements in the new release of the database relative to its first release include additional years, additional countries, two new industries (Forestry and Fishing), better country coding and coverage and, as a result, a significant increase in the number of observations: 72.5 million, compared to 35.8 million in the original release. ITPD-E-R02 can be downloaded from the USITC's Gravity Portal at \href{https://www.usitc.gov/data/gravity/itpde.htm}{https://www.usitc.gov/data/gravity/itpde.htm}. \end{abstract} \vfill \begin{flushleft} Ingo Borchert\\ University of Sussex Business School, CITP\\ \vspace{2em} Mario Larch\\ University of Bayreuth, CEPII, CESifo, GEP, ifo\\ \vspace{2em} Serge Shikher\\ Research Division, Office of Economics\\ U.S. International Trade Commission\\ gravity@usitc.gov \\ \vspace{2em} Yoto V. Yotov\\ Drexel University, ifo, CESifo\\ \end{flushleft} } % end of helvetica (arial) font \clearpage \newpage \clearpage \doublespacing \noindent \textbf{Disclaimer.} The ITPD-E is a public good that was created in response to market demand. The initial development of the database and its first update required substantial long-term efforts by the authors. Accordingly, in return for that effort, we expect two things from all users of the ITPD-E-R02. First, \underline{please cite the following two papers} if you use Release 2 of the database: \begin{itemize} \item Borchert, Ingo \& Larch, Mario \& Shikher, Serge \& Yotov, Yoto V., 2022. \emph{``The International Trade and Production Database for Estimation - Release 2 (ITPD-E-R02),''} USITC Working Paper 2022--07--A. \item Borchert, Ingo \& Larch, Mario \& Shikher, Serge \& Yotov, Yoto V., 2021. \emph{``The International Trade and Production Database for Estimation (ITPD-E),''} International Economics, Elsevier, vol. 166, pages 140--166. \end{itemize} \nocite{Borchertetal2022a} \noindent Second, if you believe to have discovered a mistake in the database or that the database can be improved by incorporating additional or more reliable data, even if only for an individual country or industry, please let us know by writing to the USITC's gravity portal e-mail address (\texttt{gravity@usitc.gov}). We will try to accommodate detection of errors, inconsistencies, and suggestions as soon as possible. Please visit \href{https://gravity.usitc.gov}{USITC's gravity portal} for updates.\\\quad\\\vspace{-1cm} \noindent \textbf{Acknowledgments.} Our team is grateful for the research support and encouragement that we have received from the United States International Trade Commission. The USITC is not in any way responsible for any errors in the ITPD-E. \clearpage \setcounter{page}{1} \clearpage \doublespacing \section{Overview and Key Features} Our objective with the original release of ITPD-E was to create a database that had the following features: (i) consistently constructed international and domestic trade flows based on administrative/raw data; (ii) detailed industry level; (iii) wide country coverage; (iv) long time-series coverage; and (v) comprehensive coverage of all broad sectors, i.e.\ full economy coverage. Therefore, in 2020, we released the \emph{International Trade and Production Database for Estimation (ITPD-E)}, cf.\ \cite{Borchertetal2021}, which covered 243 countries, 170 industries, and 17 years (2000-2016). A key feature of the ITPD-E is that it is constructed using reported administrative data and intentionally does not include information estimated by statistical techniques. Therefore, it could be used for theory-consistent disaggregated gravity estimations with international and domestic trade flows, cf.\ \cite{Borchertetal2022}. Since its introduction, the ITPD-E has been a popular public good. Based on the number and distribution of downloads of the data, we concluded that the ITPD-E has been a useful resource for many scholars, researchers, and policy makers. In addition, we have received many requests and recommendations for an update of the database. In response, we have developed the first update of the ITPD-E -- \emph{The International Trade and Production Database for Estimation - Release 2 (ITPD-E-R02).} The objective of this paper is to describe ITPD-E-R02 and to compare it with its predecessor (ITPD-E-R01), while highlighting the key features and improvements in the updated database. Relying on the same methods and capitalizing on the new releases of the original administrative/raw data sources that we used to construct ITPD-E-R01, we built a new database that includes 72,534,869 unique observations and covers the period 1986-2019 for 265 countries and 170 industries. The complete list of the industries covered in ITPD-E-R02 is included in Table \ref{ITPD-E_sectors}. Similar to ITPD-E-R01, the disaggregated industries in ITPD-E-R02 can be classified within 4 broad sectors, including \emph{`Agriculture'}, \emph{`Mining \& Energy'}, \emph{`Manufacturing'}, and \emph{`Services'}, which now have extended coverage. Specifically, the \emph{`Agriculture'} sector in the ITPD-E-R02 covers the period 1986-2019 for a total of 28 sectors. Importantly, \emph{`Agriculture'} in ITPD-E-R02 encompasses two new industries -- `Forestry' and `Fishing'. The \emph{`Mining \& Energy'} sector in ITPD-E-R02 covers the period 1988-2019 and includes 7 industries. The \emph{`Manufacturing'} sector in ITPD-E-R02 covers the same period (1988-2019) and includes 118 industries.\footnote{Two of the manufacturing industries from ITPD-E-R01 -- `Reproduction of recorded media' and `Casting of iron and steel' -- do not appear in ITPD-E-R02. The reason is that these industries did not appear in the United Nations' COMTRADE data, which we use for international trade flows. As a result, despite the addition of `Forestry' and `Fishing', the total number of industries in ITPD-E-R02 remains 170, just as in ITPD-E-R01.} Finally, the \emph{`Services'} sector in ITPD-E-R02 covers the period 2000-2019 and includes 17 industries. In addition to the standard ISO3 country codes, Release 2 of the ITPD-E identifies countries by dynamic country codes, consistent with the USITC's Dynamic Gravity Dataset (DGD) \citep{USITCGravity}. The dynamic country codes are equal to the standard ISO3 codes, except in cases where a country or territory changed its geographic boundaries, but retained its ISO3 code. In those cases, a new dynamic country code, a modified ISO3 code, is assigned.\footnote{For example, after unification of West and East Germany, the unified Germany retained the ISO3 code of West Germany, DEU. To keep track of this change in boundaries, DGD assigns the dynamic country code DEU.X to West Germany, while reserving DEU for (unified) Germany.} The complete list of the countries covered in ITPD-E-R02 is included in Table \ref{ITPD-E_countries}. ITPD-E-R02 covers 265 countries when unique dynamic country codes are counted or 256 countries when unique ISO3 country codes are counted.\footnote{There are two cases, Romania in 2002 and The Democratic Republic of the Congo in 1998, when dynamic country codes changed even though country boundaries did not. See \citet{USITCGravity} for more detail. Also, there are two countries, Cambodia and Samoa, that changed names, but not boundaries, ISO3 codes, or dynamic country codes.} The following is a brief summary of the highlights of the new version of the data (ITPD-E-R02) in relation to its original release (ITPD-E-R01): \begin{itemize} \item \emph{\textbf{Data for earlier years.}} ITPD-E-R02 includes data for years prior to 2000. Specifically, the data go back to 1986 for \emph{`Agriculture'}, and to 1988 for \emph{`Mining \& Energy'} and \emph{`Manufacturing'}. Due to administrative data limitations, we were not able to extend the data for \emph{`Services'} to years prior to 2000 because statistics on services trade flows prior to 2000 published by the WTO are not bilateral. \item \emph{\textbf{Data for recent years.}} Data for all sectors are extended to 2019 in ITPD-E-R02. \item \emph{\textbf{New industries.}} ITPD-E-R02 includes data for two new industries -- \emph{`Forestry'} and \emph{`Fishing'}, 1988-2019. Due to their nature, these industries were added under the broad sector of \emph{`Agriculture'}. \item \emph{\textbf{Improved country coverage.}} ITPD-E-R02 includes improved data coverage of some countries. For example, domestic manufacturing trade data for the United States were only available in ITPD-E R01 for the period 2000-2008, whereas in ITPD-E-R02, U.S.\ data on domestic trade flows are available for all years during the period 1997-2019. \item \emph{\textbf{Improved country coding.}} The country codes in ITPD-E-R02 are fully synchronized with USITC's \emph{``Dynamic Gravity Dataset''} (DGD), version 2.1 \citep{USITCGravity}. Consistent with DGD, ITPD-E-R02 includes dynamic country codes. % Note that dynamic country codes are not ISO3 codes. \item \emph{\textbf{New countries.}} ITPD-E-R02 covers 265 countries if the dynamic country codes are counted, or 256 countries if the ISO3 codes are counted, compared to 243 countries in ISO3 terms in \mbox{Release 1}. Most of the new countries were introduced due to the longer time coverage of ITPD-E-R02, because they no longer existed post-2000. \item \emph{\textbf{More observations.}} The total number of observations in ITPD-E-R02 is 72,534,869, i.e., 88\% more as compared to ITPD-E-R01, which had 38,518,253 observations. The number of positive trade observations in ITPD-E-R02 is 28,245,817, while ITPD-E-R01 has 18,510,257 positive trade flow observations, i.e., there are 53\% more positive trade flow observations in the new release. \end{itemize} \noindent The rest of the paper is organized as follows. Section \ref{sec_access} describes the variables and format of the ITPD-E-R02, and how to access the database. Section \ref{sec_methods_data} summarizes the methods used to construct the data and the administrative data sources. Section \ref{sec_comparison} compares ITPD-E-R02 with its predecessor, ITPD-E-R01, across various dimensions. \section{File Format, Access, and Variables \label{sec_access}} The ITPD-E databases are distributed as a comma-separated files, ITPD\_E\_RXX.csv, where XX is the release number. Thus, the initial release file is called `ITPD\_E\_R01.csv', and the update is called `ITPD\_E\_R02.csv'. Both versions of the data are available for free download at \href{https://www.usitc.gov/data/gravity/itpde.htm}{https://www.usitc.gov/data/gravity/itpde.htm}. The following is a brief description of the main categories of variables in the database, and all variables are included in Table \ref{tab:file_columns}: \begin{itemize} \item The country identifiers on the exporter and importer side, respectively, include ISO 3-letter alpha codes (`exporter\_iso3' and `importer\_iso3') and the corresponding country names (`exporter\_name' and `importer\_name'). In addition, ITPD-E-R02 includes corresponding dynamic country identifiers (`exporter\_dynamic\_code' and `importer\_dynamic\_code') that keep track of countries that alter their borders but do not receive a new ISO3 code. By design, the country coding in ITPD-E-R02 is consistent with the country coding in the USITC's \emph{``Dynamic Gravity Database''} (DGD), cf.\ \cite{USITCGravity}, which includes a series of useful bilateral and country-specific geography and economic variables and is especially suited for gravity estimations. \item The industry identifiers include industry codes and corresponding industry descriptions (`industry\_id' and `industry\_descr', respectively). While these industry variables are specific to the ITPD-E-R02, Tables \ref{tab:ITPD-E_class_ag}-\ref{tab:ITPD-E_class_services} of this document include concordances that can be used to match ITPD-E-R02 with other databases. Finally, the broad sectors in ITPD-E-R02 are described in the variable `broad\_sector'.\footnote{Note that the sector ``Mining and Energy'' is now called as such in the data. It was called ``Mining\_energy'' in Release 1.} \item The key variable in ITPD-E-R02 is `trade'. Its values are expressed in millions of current United States dollars and include international and domestic trade. Trade is \emph{international} when the exporter and the import countries are different. Trade is \emph{domestic} when the importer and the exporter are the same country. \item Finally, ITPD-E-R02 includes two flag variables. As explained in Section \ref{sec_methods}, `flag\_mirror' is an indicator variable that is equal to 1 for observations that are obtained from the mirror trade data, while `flag\_zero' shows whether the current observation contains zero or positive trade and, in case of zero, the origin of the zero. \end{itemize} \section{Methods and Sources \label{sec_methods_data}} In terms of methods and original/raw data sources, we follow closely the steps and procedures that we followed to construct the first version of the ITPD-E. \subsection{Methods \label{sec_methods}} To construct ITPD-E-R02, we follow the methods that we used to construct the original version of the data. We perform the following three principal steps, which are common across all sectors in the original and new releases of the database. \begin{itemize} \item \emph{Construct international trade.} To take full advantage of all reported international trade data we use a mirroring procedure. Given the specifics of the raw data, in our mirroring procedure for goods, we use exports reported by partner countries to fill in missing values for the corresponding import values. For services, we use reported imports to fill in missing values of exports. To denote mirrored cases, the ITPD-E-R02 includes a flag variable named $flag\_mirror$, which is an indicator that takes a value of 1 if a trade flow observation is mirrored, and 0 otherwise. \item \emph{Construct domestic trade.} Domestic trade is calculated as the difference between the (gross) value of total production and total exports. Total exports are constructed as the sum of bilateral trade for each exporting country. If we obtain a negative domestic trade value, we do not include this observation in the ITPD-E-R02. \end{itemize} \noindent For more details on the common principles and steps to construct ITPD-E-R02, we refer the reader to \cite{Borchertetal2021}. \subsection{Data Sources} The raw/administrative data sources for the first release of the ITPD-E were selected according to the following guiding criteria: (i) they should provide clear documentation; (ii) they should contain data that were not estimated by statistical procedures; and (iii) they are regularly updated. Consistent with our objectives to ensure consistency, continuity, and reproducibility of ITPD-E, for the construction of ITPD-E-R02 we relied on new versions of the same sources that we employed for the original version of the database. A summary of the various administrative data sources across all broad sectors is provided in Table \ref{tab:datasources}. \begin{itemize} \item \emph{Agriculture.} The output and trade for all industries in Agriculture, besides Forestry and Fishing, are from the Food and Agriculture Organization of the United Nations Statistics Division (FAOSTAT)\footnote{\href{https://www.fao.org/faostat/en/\#data}{https://www.fao.org/faostat/en/\#data}.}, which collects information on an annual basis for more than 245 countries. FAO obtains data from the UNSD, Eurostat, and other national authorities as needed. These data are checked for outliers and data on food aid are added to obtain total cross-border trade flows.\footnote{\href{http://www.fao.org/faostat/en/\#data/TM}{http://www.fao.org/faostat/en/\#data/TM}.} FAOSTAT's Detailed Trade Matrix reports information on agricultural bilateral trade quantities (in tons) and values (in thousands of US dollars). The Value of Agricultural Production data from the FAO contain information for at least some years for 261 geographical ``areas'' (which include country groups) and 220 different FCL items. We use gross production values in current United States dollars (the relevant file is ``Value of Agricultural Production'', \href{https://www.fao.org/faostat/en/\#data/QV}{https://www.fao.org/faostat/en/\#data/QV}). The original FAO data are classified according to the FAOSTAT Commodity List (FCL) which includes more than 600 items.\footnote{\href{http://www.fao.org/economic/ess/ess-standards/commodity/en/}{http://www.fao.org/economic/ess/ess-standards/commodity/en/}.} %Importantly, this classification can be matched to the Harmonized System Codes (HS Code) using concordance tables provided by the FAO. As we provide a database containing agriculture, mining, energy, manufacturing, and services, we have to carefully avoid double counting. Specifically, some of the FAO FCL items contain mining and manufacturing products, so we do not include these FCL items in ITPD's agriculture industries. Specifically, we classify all industries between 1500 and 1601 of ISIC rev.\ 3 as manufacturing industries. Using the FCL to HS and HS to ISIC rev.\ 3 correspondence tables, we identify the FCL items that are part of the manufacturing data.\footnote{These are FCL items 16, 18, 19, 20, 21, 22, 23, 24, 26, 28, 29, 31, 32, 34, 36, 37, 38, 39, 41, 45, 46, 48, 49, 50, 51, 57, 58, 60, 61, 64, 66, 72, 76, 80, 82, 84, 86, 90, 95, 98, 104, 109, 110, 111, 113, 114, 115, 117, 118, 119, 121, 126, 127, 129, 150, 154, 155, 158, 159, 160, 162, 163, 164, 165, 166, 167, 168, 172, 173, 175, 212, 235, 237, 238, 239, 240, 241, 244, 245, 246, 247, 252, 253, 257, 258, 259, 261, 262, 264, 266, 268, 269, 271, 272, 273, 274, 276, 278, 281, 282, 290, 291, 293, 294, 295, 297, 298, 306, 307, 313, 314, 331, 332, 334, 335, 337, 338, 340, 341, 343, 390, 391, 392, 447, 448, 450, 451, 466, 469, 471, 472, 473, 474, 475, 476, 491, 492, 496, 498, 499, 509, 510, 513, 514, 517, 518, 519, 538, 539, 562, 563, 564, 565, 575, 576, 580, 583, 584, 622, 623, 624, 625, 626, 631, 632, 633, 634, 657, 658, 659, 660, 662, 664, 665, 666, 672, 737, 753, 768, 770, 773, 774, 828, 829, 831, 840, 841, 842, 843, 845, 849, 850, 851, 852, 853, 854, 855, 867, 869, 870, 871, 872, 873, 874, 875, 877, 878, 882, 883, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 903, 904, 905, 907, 908, 909, 910, 916, 917, 919, 920, 921, 922, 927, 928, 929, 930, 947, 949, 951, 952, 953, 954, 955, 957, 958, 959, 977, 979, 982, 983, 984, 985, 988, 994, 995, 996, 997, 998, 999, 1008, 1010, 1017, 1019, 1020, 1021, 1022, 1023, 1035, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1058, 1059, 1060, 1061, 1063, 1064, 1065, 1066, 1069, 1073, 1074, 1075, 1080, 1081, 1089, 1097, 1098, 1102, 1103, 1104, 1105, 1108, 1109, 1111, 1112, 1127, 1128, 1129, 1130, 1141, 1151, 1158, 1160, 1163, 1164, 1166, 1167, 1168, 1172, 1173, 1174, 1175, 1186, 1187, 1221, 1222, 1223, 1225, 1241, 1242, 1243, 1273, 1274, 1275, 1276, 1277, and 1296.} Note that these FCL items typically do not have matching production data in the FAO's database. Some FCL items could not be uniquely matched to broad sectors. In these cases, we allocated FCL items according the number of constituent HS lines.\footnote{This leads in dropping of industries with FCL items 653, 868, 948, 978, 1018, 1036, 1232, and 1259. We kept the following FCL items in agriculture: 667, 777, 780, 782, 826, 987, 1009, and 1293.} We also dropped industries we could not match to any ISIC or HS code\footnote{Specifically, we could not match FCL items 10, 30, 464, 944, 972, 1012, 1032, 1055, 1070, 1077, 1084, 1087, 1094, 1120, 1122, 1124, 1137, 1144, 1154, 1159, and 1161.} and industries with FCL item codes above 1296, which are aggregates and industries such as fertilizers, pesticides, and machinery, belonging to one of the other broad sectors. Table \ref{tab:ITPD-E_class_ag} includes the correspondence between ITPD-E agricultural industries and FCL items. \item \emph{Forestry and Fishing.} These two industries are new in ITPD-E-R02. Even though they are ultimately treated as part of the broad sector \emph{`Agriculture'}, the data sources for these two industries are different from the data sources for the rest of industries in \emph{`Agriculture'}. Since FAOSTAT, which is the main data source for \emph{`Agriculture'}, does not cover `Forestry' and `Fishing', we had to look for other sources of data. Specifically, international trade data for `Forestry' and `Fishing' come from the United Nations' Commodity Trade Statistics Database (COMTRADE),\footnote{As noted below, we rely on COMTRADE for international trade data in \emph{`Mining \& Energy'} and \emph{`Manufacturing'} too. A description of COMTRADE can be found at \href{https://comtrade.un.org}{https://comtrade.un.org}.} while production data come from the UN National Accounts database (UNSNA); specifically, the SNA's ``\mbox{Table 2.6} Output, gross value added and fixed assets by industries at current prices (ISIC Rev.4).''\footnote{\href{http://data.un.org/Data.aspx?d=SNA\&f=group\_code\%3a206}{http://data.un.org/Data.aspx?d=SNA\&f=group\_code\%3a206}.} `Forestry' corresponds to industry code A02, ``Forestry and Logging'', in ISIC revisions 3 and 4. `Fishing' corresponds to industry code A03, ``Fishing and Aquaculture'', in ISIC revision 4 and industry code B05 in ISIC revision 3. Availability of trade data predetermined the first year of coverage for the `Forestry' and `Fishing' industries as 1988. \item \emph{Mining \& Energy.} International trade data for the \emph{`Mining \& Energy'} sector come from COMTRADE, and were obtained in ISIC rev.\ 3. Availability of trade data determined 1988 as the first year of coverage for \emph{`Mining \& Energy'}. Production data for \emph{`Mining \& Energy'} come from the ``MINSTAT - Mining and Utilities Statistics Database'' dataset of the United Nations Industrial Development Organization (UNIDO). To take full advantage of MINSTAT, and to ensure maximum coverage in ITPD-E-R02, we use the ISIC rev.\ 3 and ISIC rev.\ 4 versions of MINSTAT. Availability of production data determined the last year of coverage for \emph{`Mining \& Energy'} as 2019. A list of the ITPD-E mining and energy industries, together with the concordance that we created between ISIC rev.\ 3, ISIC rev.\ 4, and ITPD-E-R02 appear in Table \ref{tab:ITPD-E_class_mining}. \item \emph{Manufacturing.} International trade flows data come from COMTRADE, and were obtained in ISIC rev.\ 3. Availability of trade data determined 1988 as the first year of coverage for \emph{`Manufacturing'}. The source for manufacturing production data is the United Nations Industrial Statistics (INDSTAT) database (\href{http://stat.unido.org}{http://stat.unido.org}), and the data come in two versions -- ISIC rev.\ 3 and ISIC rev.\ 4. To ensure maximum coverage, we construct the manufacturing production data in two steps. First, for each revision of ISIC, we combine the output data at the 3-digit level with the data at the 4-digit level. Then, we combine the data from the two ISIC revisions by aggregating the 4-digit ISIC classifications up in order to ensure matching. The concordance that we created appears in Table \ref{tab:ITPD-E_class_manuf}. \item \emph{Services.} For international trade data, we augment the WTO-UNCTAD-ITC Annual Trade in Services dataset\footnote{\href{http://stats.wto.org/assets/UserGuide/services\_annual\_dataset.zip}{http://stats.wto.org/assets/UserGuide/services\_annual\_dataset.zip}.} with services trade statistics from the UN Trade in Services (UN-TSD) Database as incorporated into COMTRADE.\footnote{\href{https://comtrade.un.org/data/}{https://comtrade.un.org/data/}.} As before, the reasons are twofold: firstly, to achieve comprehensive coverage of ITPD-E from the year 2000 onwards, since the WTO-UNCTAD-ITC dataset as the main data source only commences in 2005, and second to supplement bilateral trade flow observation in overlapping years that are missing in the WTO-UNCTAD-ITC dataset. That said, services trade data in Release 2 come with the following significant improvements. Due to new trade flow and gross output data, the services part of the R02 update exhibits nearly complete coverage of the year 2019 and as such represents the most recent statistics currently available.\footnote{Information for years prior to 2000, potentially reaching back to 1981, are now included in the latest vintage of the WTO-UNCTAD-ITC dataset; however, these flows are not bilateral. As such, we will have to disregard these flows for the R02 update.} Compared to the R01 release, another new feature of the WTO-UNCTAD-ITC dataset is that about half of the raw data are reported zeroes, i.e.\ unlike in prior releases, zero trade flows now seem to have been captured more systematically, and `true' reported zero flows are identifiable in the data through a flag. At the same time, the WTO-UNCTAD-ITC dataset does no longer contain information on the sources of the statistical information. By comparison, in the R01 release the overwhelming majority of data had come from Eurostat (69\%) and some 17\% from the OECD. The data contain both reported import flows and reported export flows, which opens up the possibility of an improved mirroring protocol. For both export and import flows, the data combine two different data types: annual trade broken out by sector but not by partner, over the period 1980-2013, and annual trade broken out by sector and partner, over the period 2005-2019. These two kinds of data flows correspond to different ways and sources of collecting the raw data as the former set of observations is in EPOBS 2002 (BPM5) whereas the latter set of observations is in EPOBS 2010 (BPM6). Since we will discard the BPM5 (non-bilateral) data, we expect that, as in the R01 release, augmentation of services trade data for the period 2000-2010 from the UN Trade in Services dataset will bring considerable benefits in terms of coverage and completeness. We obtain information on gross output at basic prices from the UN SNA dataset, namely ``\mbox{Table 2.6} Output, gross value added and fixed assets by industries at current prices (ISIC Rev.4).''\footnote{\href{http://data.un.org/Data.aspx?d=SNA\&f=group\_code\%3a206}{http://data.un.org/Data.aspx?d=SNA\&f=group\_code\%3a206}.} A raw data problem has been identified with regard to domestic trade flows in Belarus (BLR), which initially appeared to be implausibly large prior to 2015. Upon investigation, we found that the Belarusian currency is subject to two different currency re-denomination (1:1000 prior to 2015 and 1:10000 from 2016 onwards). Since output figures in local currency (LCU) shrink by four decimals as of 2016, it appears as if the re-denomination has not been applied in earlier years (although presumably it should have) but has been applied as indicated commencing in 2016. The IMF exchange rate series for Belarus is smooth around 2015-16 and does not exhibit a jump by a factor of 10. In order to ensure consistency of the value of trade flows in R02, output data for Belarus have been discarded. This issue also afflicts the R01 services trade data and an erratum to this effect will be published. \end{itemize} \noindent For a more detailed background on the data sources and their specific usage for the construction of ITPD-E-R02, we refer the reader to \cite{Borchertetal2021}. \section{\label{sec_comparison} A comparison of ITPD-E Release 2 and Release 1} This section compares ITPD-E-R02 with the first release of the data. Tables \ref{tab:compare_totals}-\ref{tab:compare_by_country} summarize the differences between the two releases across different dimensions. All four tables reflect the entirety of trade flows contained in each release, i.e.\ domestic and international trade.\footnote{Exceptions are industries IDs 154, 155, 161, 167 and 168, which are services industries with no domestic production equivalent. Hence, entries for these five industries reflect international trade only.} Table \ref{tab:compare_totals} compares the total number of observations in the two releases. Release 2 has significantly more observations in total, about 72.5 million, compared to 38.5 million in Release 1. Most of these additional observations come from additional years covered by Release 2. A small number of observations, less than 1 million, was present in Release 1 but is no longer in Release 2. These observations likely disappeared because they were reclassified to a different country, industry, or year. Table \ref{tab:compare_by_year} compares the number of observations across Releases 1 and 2 \emph{by year}. It is apparent that most of the additional 35 million observations in Release 2 arise from additional years now covered by Release 2 relative to Release 1. In 1986 and 1987, only Agriculture industries 1-26 are covered, hence the low number of observations. Starting in 1988, all goods industries are covered. The number of observations increases between 1988 and mid-1990s as more and more countries report more data to the UN. The number of observations increases again in the year 2000 as services data become available. In that regard, one of the reasons why the value of reported trade exhibits a very substantial jump between 1999 and 2000---from 16.3 to 43.3 trillion---is that domestic trade in services is much larger than domestic trade in goods. Comparing the number of observations in the years that are covered in both Releases 1 and 2 (i.e.\ 2000-2016), we see that Release 2 has more observations per year. This is due to the two additional industries now included in Release 2, Forestry and Fishing, and also due to improved data coverage in the original data sources that we use.\footnote{Even though the number of industries does not change between releases 1 and 2, the two new industries have many more observations than the two that were removed.} Table \ref{tab:compare_by_industry} compares the number of observations across Releases 1 and 2 \emph{by industry}. The number of observations for each industry is greater in Release 2. There are also two additional industries in Release 2, Forestry (27) and Fishing (28). Therefore, industry IDs diverge after number 26 between Releases 1 and 2. At the same time, Release 2 drops two manufacturing industries that were present in Release 1, namely `Reproduction of recorded media' (77) and `Casting of iron and steel' (103). We removed these two industries from the manufacturing sector because they have no international trade data. The largest industries by value tend to be concentrated in the Services sector, which reflects the fact that a substantial share of domestic value added typically is in services industries (up to 70-80\% in advanced economies), combined with the fact that table entries include domestic trade flows. Outside services, the largest industries by value are 'Motor vehicles' (138) and 'Extraction of petroleum and gas' (31) and 'Refined petroleum products' (80), respectively. Table \ref{tab:compare_by_country} shows the coverage across Releases 1 and 2 \emph{by country}. This table also makes it easy to see which countries were added in Release 2 compared to Release 1. Because of the addition of earlier years, some of these new entries are countries that existed prior to 2000, such as, for example, Yugoslavia. The United States is by a wide margin the largest single economy in the database, accounting for 26\% of the total value of trade (across all years and industries) in Release 2. The second and third largest economies are the two Asia-Pacific powerhouses China (9.2\%) and Japan (9.0\%), followed by Germany (6.6\%). It is interesting to note that the relative value share of the US has remained roughly the same, whereas Japan's and Germany's shares have fallen in Release 2 compared to Release 1, reflecting the steep rise of China (via the additions of new years), whose value of trade has nearly doubled. Again, since domestic trade flows are included, value shares and ranks reflect economic size more than trade openness. The global reach of Release 2 can also be seen by the fact that major emerging economies such as India or Brazil now account for 2\% or more of global trade. \section{Conclusions} With more years and more countries, Release 2 of ITPD-E offers nearly twice as many observations for trade and production as its predecessor (72.5 million, or an increase by 88\%). It features global coverage and an unprecedented level of sectoral disaggregation, covering all economic activity. The addition of earlier years, starting in 1986/88, for Agriculture, Mining and Manufacturing will enable analyses with longer time-series that were not possible with the first Release. Thus we hope that ITPD-E R02 will prove a useful resource for a wide range of econometric analyses including structural gravity estimation. We plan to complement the ITPD database for estimation with a companion dataset suitable for general equilibrium analysis and simulation (ITPD-S). \clearpage \bibliographystyle{aea} \bibliography{references} \clearpage \clearpage {\tiny\singlespacing \begin{longtable}{rll} \caption{ \label{ITPD-E_sectors} ITPD-E-R02: Industry Coverage}\\ \hline\hline ID & Industry Description & Broad Sector \\\hline \endfirsthead \hline ID & Industry Description & Broad Sector \\\hline \endhead \hline \multicolumn{3}{r}{{Continued on next page}}\\ \endfoot \endlastfoot 1 & Wheat & Agriculture \\ 2 & Rice (raw) & Agriculture \\ 3 & Corn & Agriculture \\ 4 & Other cereals & Agriculture \\ 5 & Cereal products & Agriculture \\ 6 & Soybeans & Agriculture \\ 7 & Other oilseeds (excluding peanuts) & Agriculture \\ 8 & Animal feed ingredients and pet foods & Agriculture \\ 9 & Raw and refined sugar and sugar crops & Agriculture \\ 10 & Other sweeteners & Agriculture \\ 11 & Pulses and legumes, dried, preserved & Agriculture \\ 12 & Fresh fruit & Agriculture \\ 13 & Fresh vegetables & Agriculture \\ 14 & Prepared fruits and fruit juices & Agriculture \\ 15 & Prepared vegetables & Agriculture \\ 16 & Nuts & Agriculture \\ 17 & Live Cattle & Agriculture \\ 18 & Live Swine & Agriculture \\ 19 & Eggs & Agriculture \\ 20 & Other meats, livestock products, and live animals & Agriculture \\ 21 & Cocoa and cocoa products & Agriculture \\ 22 & Beverages, nec & Agriculture \\ 23 & Cotton & Agriculture \\ 24 & Tobacco leaves and cigarettes & Agriculture \\ 25 & Spices & Agriculture \\ 26 & Other agricultural products, nec & Agriculture \\ 27 & Forestry & Agriculture \\ 28 & Fishing & Agriculture \\ 29 & Mining of hard coal & Mining and Energy \\ 30 & Mining of lignite & Mining and Energy \\ 31 & Extraction crude petroleum and natural gas & Mining and Energy \\ 32 & Mining of iron ores & Mining and Energy \\ 33 & Other mining and quarring & Mining and Energy \\ 34 & Electricity production, collection, and distribution & Mining and Energy \\ 35 & Gas production and distribution & Mining and Energy \\ 36 & Processing/preserving of meat & Manufacturing \\ 37 & Processing/preserving of fish & Manufacturing \\ 38 & Processing/preserving of fruit \& vegetables & Manufacturing \\ 39 & Vegetable and animal oils and fats & Manufacturing \\ 40 & Dairy products & Manufacturing \\ 41 & Grain mill products & Manufacturing \\ 42 & Starches and starch products & Manufacturing \\ 43 & Prepared animal feeds & Manufacturing \\ 44 & Bakery products & Manufacturing \\ 45 & Sugar & Manufacturing \\ 46 & Cocoa chocolate and sugar confectionery & Manufacturing \\ 47 & Macaroni noodles \& similar products & Manufacturing \\ 48 & Other food products n.e.c. & Manufacturing \\ 49 & Distilling rectifying \& blending of spirits & Manufacturing \\ 50 & Wines & Manufacturing \\ 51 & Malt liquors and malt & Manufacturing \\ 52 & Soft drinks; mineral waters & Manufacturing \\ 53 & Tobacco products & Manufacturing \\ 54 & Textile fibre preparation; textile weaving & Manufacturing \\ 55 & Made-up textile articles except apparel & Manufacturing \\ 56 & Carpets and rugs & Manufacturing \\ 57 & Cordage rope twine and netting & Manufacturing \\ 58 & Other textiles n.e.c. & Manufacturing \\ 59 & Knitted and crocheted fabrics and articles & Manufacturing \\ 60 & Wearing apparel except fur apparel & Manufacturing \\ 61 & Dressing \& dyeing of fur; processing of fur & Manufacturing \\ 62 & Tanning and dressing of leather & Manufacturing \\ 63 & Luggage handbags etc.; saddlery \& harness & Manufacturing \\ 64 & Footwear & Manufacturing \\ 65 & Sawmilling and planing of wood & Manufacturing \\ 66 & Veneer sheets plywood particle board etc. & Manufacturing \\ 67 & Builders' carpentry and joinery & Manufacturing \\ 68 & Wooden containers & Manufacturing \\ 69 & Other wood products; articles of cork/straw & Manufacturing \\ 70 & Pulp paper and paperboard & Manufacturing \\ 71 & Corrugated paper and paperboard & Manufacturing \\ 72 & Other articles of paper and paperboard & Manufacturing \\ 73 & Publishing of books and other publications & Manufacturing \\ 74 & Publishing of newspapers journals etc. & Manufacturing \\ 75 & Publishing of recorded media & Manufacturing \\ 76 & Other publishing & Manufacturing \\ 77 & Printing & Manufacturing \\ 78 & Service activities related to printing & Manufacturing \\ 79 & Coke oven products & Manufacturing \\ 80 & Refined petroleum products & Manufacturing \\ 81 & Processing of nuclear fuel & Manufacturing \\ 82 & Basic chemicals except fertilizers & Manufacturing \\ 83 & Fertilizers and nitrogen compounds & Manufacturing \\ 84 & Plastics in primary forms; synthetic rubber & Manufacturing \\ 85 & Pesticides and other agro-chemical products & Manufacturing \\ 86 & Paints varnishes printing ink and mastics & Manufacturing \\ 87 & Pharmaceuticals medicinal chemicals etc. & Manufacturing \\ 88 & Soap cleaning \& cosmetic preparations & Manufacturing \\ 89 & Other chemical products n.e.c. & Manufacturing \\ 90 & Man-made fibres & Manufacturing \\ 91 & Rubber tyres and tubes & Manufacturing \\ 92 & Other rubber products & Manufacturing \\ 93 & Plastic products & Manufacturing \\ 94 & Glass and glass products & Manufacturing \\ 95 & Pottery china and earthenware & Manufacturing \\ 96 & Refractory ceramic products & Manufacturing \\ 97 & Struct.non-refractory clay; ceramic products & Manufacturing \\ 98 & Cement lime and plaster & Manufacturing \\ 99 & Articles of concrete cement and plaster & Manufacturing \\ 100 & Cutting shaping \& finishing of stone & Manufacturing \\ 101 & Other non-metallic mineral products n.e.c. & Manufacturing \\ 102 & Basic iron and steel & Manufacturing \\ 103 & Basic precious and non-ferrous metals & Manufacturing \\ 104 & Structural metal products & Manufacturing \\ 105 & Tanks reservoirs and containers of metal & Manufacturing \\ 106 & Steam generators & Manufacturing \\ 107 & Cutlery hand tools and general hardware & Manufacturing \\ 108 & Other fabricated metal products n.e.c. & Manufacturing \\ 109 & Engines \& turbines (not for transport equipment) & Manufacturing \\ 110 & Pumps compressors taps and valves & Manufacturing \\ 111 & Bearings gears gearing \& driving elements & Manufacturing \\ 112 & Ovens furnaces and furnace burners & Manufacturing \\ 113 & Lifting and handling equipment & Manufacturing \\ 114 & Other general purpose machinery & Manufacturing \\ 115 & Agricultural and forestry machinery & Manufacturing \\ 116 & Machine tools & Manufacturing \\ 117 & Machinery for metallurgy & Manufacturing \\ 118 & Machinery for mining \& construction & Manufacturing \\ 119 & Food/beverage/tobacco processing machinery & Manufacturing \\ 120 & Machinery for textile apparel and leather & Manufacturing \\ 121 & Weapons and ammunition & Manufacturing \\ 122 & Other special purpose machinery & Manufacturing \\ 123 & Domestic appliances n.e.c. & Manufacturing \\ 124 & Office accounting and computing machinery & Manufacturing \\ 125 & Electric motors generators and transformers & Manufacturing \\ 126 & Electricity distribution \& control apparatus & Manufacturing \\ 127 & Insulated wire and cable & Manufacturing \\ 128 & Accumulators primary cells and batteries & Manufacturing \\ 129 & Lighting equipment and electric lamps & Manufacturing \\ 130 & Other electrical equipment n.e.c. & Manufacturing \\ 131 & Electronic valves tubes etc. & Manufacturing \\ 132 & TV/radio transmitters; line comm. apparatus & Manufacturing \\ 133 & TV and radio receivers and associated goods & Manufacturing \\ 134 & Medical surgical and orthopaedic equipment & Manufacturing \\ 135 & Measuring/testing/navigating appliances etc. & Manufacturing \\ 136 & Optical instruments \& photographic equipment & Manufacturing \\ 137 & Watches and clocks & Manufacturing \\ 138 & Motor vehicles & Manufacturing \\ 139 & Automobile bodies trailers \& semi-trailers & Manufacturing \\ 140 & Parts/accessories for automobiles & Manufacturing \\ 141 & Building and repairing of ships & Manufacturing \\ 142 & Building/repairing of pleasure/sport. boats & Manufacturing \\ 143 & Railway/tramway locomotives \& rolling stock & Manufacturing \\ 144 & Aircraft and spacecraft & Manufacturing \\ 145 & Motorcycles & Manufacturing \\ 146 & Bicycles and invalid carriages & Manufacturing \\ 147 & Other transport equipment n.e.c. & Manufacturing \\ 148 & Furniture & Manufacturing \\ 149 & Jewellery and related articles & Manufacturing \\ 150 & Musical instruments & Manufacturing \\ 151 & Sports goods & Manufacturing \\ 152 & Games and toys & Manufacturing \\ 153 & Other manufacturing n.e.c. & Manufacturing \\ 154 & Manufacturing services on physical inputs & Services \\ 155 & Maintenance and repair services n.i.e. & Services \\ 156 & Transport & Services \\ 157 & Travel & Services \\ 158 & Construction & Services \\ 159 & Insurance and pension services & Services \\ 160 & Financial services & Services \\ 161 & Charges for use of intellectual property & Services \\ 162 & Telecom, computer, information services & Services \\ 163 & Other business services & Services \\ 164 & Heritage and recreational services & Services \\ 165 & Health services & Services \\ 166 & Education services & Services \\ 167 & Government goods and services n.i.e. & Services \\ 168 & Services not allocated & Services \\ 169 & Trade-related services & Services \\ 170 & Other personal services & Services \\ \hline \hline \multicolumn{3}{p{0.55\linewidth}}{\scriptsize\textbf{Notes}: This table lists the 170 industries in ITPD-E-R02. Column (1) lists ITPD-E-R02 ID codes for each of the industries. The corresponding industry descriptions are in Column (2). Column (3) includes the broad sectoral descriptions. See text for further details.}\\ \end{longtable}} \clearpage {\tiny\singlespacing \begin{longtable}{ll} \caption{ \label{ITPD-E_countries} ITPD-E-R02: Country Coverage}\\ \hline\hline Dynamic Country Code & Country Name \\ \hline \endfirsthead \hline Dynamic Country Code & Country Name \\ \hline \endhead \hline \multicolumn{2}{r}{{Continued on next page}}\\ \endfoot \endlastfoot ABW & Aruba \\ AFG & Afghanistan \\ AGO & Angola \\ AIA & Anguilla \\ ALB & Albania \\ AND & Andorra \\ ANT.X & Netherlands Antilles \\ ARE & United Arab Emirates \\ ARG & Argentina \\ ARM & Armenia \\ ASM & American Samoa \\ ATA & Antarctica \\ ATF & French Southern Territories \\ ATG & Antigua and Barbuda \\ AUS & Australia \\ AUT & Austria \\ AZE & Azerbaijan \\ BDI & Burundi \\ BEL & Belgium \\ BEN & Benin \\ BES & Bonaire, Sint Eustatius and Saba \\ BFA & Burkina Faso \\ BGD & Bangladesh \\ BGR & Bulgaria \\ BHR & Bahrain \\ BHS & Bahamas, The \\ BIH & Bosnia and Herzegovina \\ BLM & Saint Barthelemy \\ BLR & Belarus \\ BLX & Belgium-Luxembourg \\ BLZ & Belize \\ BMU & Bermuda \\ BOL & Bolivia \\ BRA & Brazil \\ BRB & Barbados \\ BRN & Brunei \\ BTN & Bhutan \\ BUR & Burma \\ BVT & Bouvet Island \\ BWA & Botswana \\ CAF & Central African Republic \\ CAN & Canada \\ CCK & Cocos (Keeling) Islands \\ CHE & Switzerland \\ CHL & Chile \\ CHN & China \\ CIV & Cote d'Ivoire \\ CMR & Cameroon \\ COD & Congo, Democratic Republic of the \\ COG & Congo, Republic of the \\ COK & Cook Islands \\ COL & Colombia \\ COM & Comoros \\ CPV & Cape Verde \\ CRI & Costa Rica \\ CSK & Czechoslovakia \\ CUB & Cuba \\ CUW & Curacao \\ CXR & Christmas Island \\ CYM & Cayman Islands \\ CYP & Cyprus \\ CZE & Czech Republic \\ DDR & German Democratic Republic \\ DEU & Germany \\ DEU.X & West Germany \\ DJI & Djibouti \\ DMA & Dominica \\ DNK & Denmark \\ DOM & Dominican Republic \\ DZA & Algeria \\ ECU & Ecuador \\ EGY & Egypt, Arab Rep. \\ ERI & Eritrea \\ ESH & Western Sahara \\ ESP & Spain \\ EST & Estonia \\ ETF & Ethiopia (includes Eritrea) \\ ETH & Ethiopia (excludes Eritrea) \\ FIN & Finland \\ FJI & Fiji \\ FLK & Falkland Islands \\ FRA & France \\ FRE & Free Zones \\ FRO & Faeroe Islands \\ FSM & Micronesia, Federated States of \\ GAB & Gabon \\ GAZ & Gaza Strip \\ GBR & United Kingdom \\ GEO & Georgia \\ GHA & Ghana \\ GIB & Gibraltar \\ GIN & Guinea \\ GLP & Guadeloupe \\ GMB & Gambia, The \\ GNB & Guinea-Bissau \\ GNQ & Equatorial Guinea \\ GRC & Greece \\ GRD & Grenada \\ GRL & Greenland \\ GTM & Guatemala \\ GUF & French Guiana \\ GUM & Guam \\ GUY & Guyana \\ HKG & Hong Kong \\ HMD & Heard Island and McDonald Islands \\ HND & Honduras \\ HRV & Croatia \\ HTI & Haiti \\ HUN & Hungary \\ IDN & Indonesia \\ IMN & Isle of Man \\ IND & India \\ IOT & British Indian Ocean Ter. \\ IRL & Ireland \\ IRN & Iran \\ IRQ & Iraq \\ ISL & Iceland \\ ISR & Israel \\ ITA & Italy \\ JAM & Jamaica \\ JOR & Jordan \\ JPN & Japan \\ KAZ & Kazakhstan \\ KEN & Kenya \\ KGZ & Kyrgyzstan \\ KHM & Kampuchea (until 1988), Cambodia(1989-present) \\ KIR.X & Kiribati \\ KNA & Saint Kitts and Nevis \\ KOR & Korea, South \\ KWT & Kuwait \\ LAO & Laos \\ LBN & Lebanon \\ LBR & Liberia \\ LBY & Libya \\ LCA & Saint Lucia \\ LIE & Liechtenstein \\ LKA & Sri Lanka \\ LSO & Lesotho \\ LTU & Lithuania \\ LUX & Luxembourg \\ LVA & Latvia \\ MAC & Macao \\ MAR & Morocco \\ MCO & Monaco \\ MDA & Moldova \\ MDG & Madagascar \\ MDV & Maldives \\ MEX & Mexico \\ MHL & Marshall Islands \\ MKD & Macedonia \\ MLI & Mali \\ MLT & Malta \\ MMR & Myanmar \\ MNE & Montenegro \\ MNG & Mongolia \\ MNP & Northern Marianas \\ MOZ & Mozambique \\ MRT & Mauritania \\ MSR & Montserrat \\ MTQ & Martinique \\ MUS & Mauritius \\ MWI & Malawi \\ MYS.Y & Malaysia \\ MYT & Mayotte \\ NAM & Namibia \\ NCL & New Caledonia \\ NER & Niger \\ NFK & Norfolk Island \\ NGA & Nigeria \\ NIC & Nicaragua \\ NIU & Niue \\ NLD & Netherlands \\ NOR & Norway \\ NPL & Nepal \\ NRU & Nauru \\ NTZ & Neutral Zone \\ NZL & New Zealand \\ OMN & Oman \\ PAK.X & Pakistan \\ PAN.X & Panama \\ PCN & Pitcairn \\ PER & Peru \\ PHL & Philippines \\ PLW & Palau \\ PNG & Papua New Guinea \\ POL & Poland \\ PRI & Puerto Rico \\ PRK & Korea, North \\ PRT & Portugal \\ PRY & Paraguay \\ PSE & Palestine \\ PYF & French Polynesia \\ QAT & Qatar \\ REU & Reunion \\ ROM & Romania \\ ROU & Romania \\ RUS & Russia \\ RWA & Rwanda \\ SAU & Saudi Arabia \\ SAU.X & Saudi Arabia \\ SCG & Serbia and Montenegro \\ SDN & Sudan \\ SDN.X & Sudan \\ SEN & Senegal \\ SGP & Singapore \\ SGS & South Georgia and South Sandwich Islands \\ SHN & Saint Helena, Ascension, and Tristan da Cunha \\ SLB & Solomon Islands \\ SLE & Sierra Leone \\ SLV & El Salvador \\ SMR & San Marino \\ SOM & Somalia \\ SPM & Saint Pierre and Miquelon \\ SRB & Serbia \\ SRB.X & Serbia \\ SSD & South Sudan \\ STP & Sao Tome and Principe \\ SUR & Suriname \\ SVK & Slovakia \\ SVN & Slovenia \\ SVU & Soviet Union \\ SWE & Sweden \\ SWZ & Swaziland \\ SXM & Sint Maarten \\ SYC & Seychelles \\ SYR & Syria \\ TCA & Turks and Caicos Islands \\ TCD & Chad \\ TGO & Togo \\ THA & Thailand \\ TJK & Tajikistan \\ TKL & Tokelau \\ TKM & Turkmenistan \\ TLS & East Timor \\ TON & Tonga \\ TTO & Trinidad and Tobago \\ TUN & Tunisia \\ TUR & Turkey \\ TUV & Tuvalu \\ TWN & Taiwan \\ TZA & Tanzania \\ UGA & Uganda \\ UKR & Ukraine \\ UMI & U.S. Minor Outlying Islands \\ URY & Uruguay \\ USA & United States \\ UZB & Uzbekistan \\ VAT & Holy See \\ VCT & Saint Vincent and the Grenadines \\ VEN & Venezuela \\ VGB & British Virgin Islands \\ VIR & U.S. Virgin Islands \\ VNM.X & Vietnam \\ VUT & Vanuatu \\ WLF & Wallis and Futuna Islands \\ WSM & Western Samoa (until 1996), Samoa (1997-present) \\ YEM & Yemen, North \\ YEM.X & Yemen \\ YMD & Yemen, South \\ YUG & Yugoslavia \\ ZAF & South Africa \\ ZAF.X & South Africa \\ ZAR & Zaire \\ ZMB & Zambia \\ ZWE & Zimbabwe \\ \hline\hline \multicolumn{2}{p{0.55\linewidth}}{\scriptsize\textbf{Notes}: This table lists the 265 countries/regions covered in ITPD-E-R02 (in Column 2), and their corresponding Dynamic Country Codes (in Column 1). Two countries in the table (Cambodia and Samoa) have changed their names between 1986 and 2019 while keeping the same Dynamic Country Code. See text for further details.}\\ \end{longtable}} \clearpage \begin{table}[tbp]\centering \caption{\label{tab:file_columns}Variables in ITPD-E-R02 -- Data File Columns} \begin{tabular}{ll} \hline Column name & Column description \\ \hline exporter\_iso3 & ISO 3-letter alpha code of the exporter\\ exporter\_name & Name of the exporter \\ importer\_iso3 & ISO 3-letter alpha code of the importer \\ importer\_name & Name of the importer \\ exporter\_dynamic\_code & Dynamic alpha code of the exporter based on DGD\\ importer\_dynamic\_code & Dynamic alpha code of the importer based on DGD\\ year & Year \\ industry\_id & ITPD industry code \\ industry\_descr & ITPD industry description \\ broad\_sector & Broad sector description\\ trade & Trade flows in million of current US dollars\\ flag\_mirror & Flag indicator, 1 if trade mirror value is used \\ flag\_zero & Flag indicator: \\ & `p' if positive trade \\ & `r' if the raw data contained zero \\ & `u' missing (unknown, assigned zero) \\ \hline \end{tabular} \end{table} \clearpage \begin{table}[!htbp] \centering \caption{Data Sources} \begin{tabular}{lll} \toprule Broad sector & International trade & Production \\ \midrule Agriculture & \href{http://faostat3.fao.org/home/E}{FAOSTAT} & \href{http://www.fao.org/faostat/en/\#data}{FAOSTAT} \\ (industries 1-26) & Detailed Trade Matrix & Value of Agricultural Production\\ & & \\ Agriculture & \href{http://comtrade.un.org}{COMTRADE} & \href{http://data.un.org/Explorer.aspx?d=SNA}{UN National Accounts Statistics}\\ (Forestry, Fishing) & (United Nations International & \\ & Trade Statistics Database) & \\ & & \\ Mining and energy & \href{http://comtrade.un.org}{COMTRADE} & \href{http://www.world-mining-data.info/}{MINSTAT} \\ & & (Mining and Utilities Statistics \\ & & Database) from UNIDO \\ & & (United Nations Industrial \\ & & Development Organization) \\ & & \\ Manufacturing & \href{http://comtrade.un.org}{COMTRADE} & \href{http://stat.unido.org}{INDSTAT} \\ & & (Industrial Statistics Database) \\ & & from UNIDO \\ & & \\ Services & \href{https://www.wto.org/english/res\_e/statis\_e/trade\_datasets\_e.htm}{WTO-UNCTAD-ITC} Annual & \href{http://data.un.org/Explorer.aspx?d=SNA}{UN National Accounts Statistics} \\ & Trade in Services Database & \\ & \href{https://comtrade.un.org/data}{UN TSD} (Trade in Services & \\ & Database) via COMTRADE & \\ \bottomrule \multicolumn{3}{p{0.95\linewidth}}{\footnotesize\textbf{Notes}: This table provides a summary of the various administrative data sources across the four broad sectors in the ITPD-E-R02. Please see main text for further details.} \end{tabular}% \label{tab:datasources}% \end{table} \clearpage {\tiny\singlespacing \begin{longtable}{c l c l} \caption{\label{tab:ITPD-E_class_ag}USITC Agricultural Classification}\\\hline\hline ITPD-E Code & ITPD-E Description & FCL Item Code & FCL Title \\ \hline \endfirsthead \hline ITPD-E Code & ITPD-E Description & FCL Item Code & FCL Title \\ \hline \endhead \hline \multicolumn{4}{r}{{Continued on next page}}\\ \endfoot \endlastfoot 1 & Wheat & 15 & Wheat \\ 2 & Rice (raw) & 27 & Rice, paddy \\ 3 & Corn & 56 & Maize \\ 4 & Other cereals & 44 & Barley \\ 4 & Other cereals & 71 & Rye \\ 4 & Other cereals & 75 & Oats \\ 4 & Other cereals & 79 & Millet \\ 4 & Other cereals & 83 & Sorghum \\ 4 & Other cereals & 89 & Buckwheat \\ 4 & Other cereals & 92 & Quinoa \\ 4 & Other cereals & 94 & Fonio \\ 4 & Other cereals & 97 & Triticale \\ 4 & Other cereals & 101 & Canary seed \\ 4 & Other cereals & 103 & Mixed grain \\ 4 & Other cereals & 108 & Cereals, nes \\ 5 & Cereal products & 17 & Bran of Wheat \\ 5 & Cereal products & 59 & Bran of Maize \\ 5 & Cereal products & 81 & Bran of Millet \\ 5 & Cereal products & 85 & Bran of Sorghum \\ 5 & Cereal products & 91 & Bran of Buckwheat \\ 5 & Cereal products & 96 & Bran of Fonio \\ 6 & Soybeans & 236 & Soybeans \\ 7 & Other oilseeds (exc.\ peanuts) & 242 & Groundnuts, in shell \\ 7 & Other oilseeds (exc.\ peanuts) & 243 & Groundnuts, Shelled \\ 7 & Other oilseeds (exc.\ peanuts) & 249 & Coconuts \\ 7 & Other oilseeds (exc.\ peanuts) & 250 & Coconuts, Desiccated \\ 7 & Other oilseeds (exc.\ peanuts) & 251 & Copra \\ 7 & Other oilseeds (exc.\ peanuts) & 254 & Oil palm fruit \\ 7 & Other oilseeds (exc.\ peanuts) & 256 & Palm kernels \\ 7 & Other oilseeds (exc.\ peanuts) & 263 & Karite Nuts (Sheanuts) \\ 7 & Other oilseeds (exc.\ peanuts) & 265 & Castor Beans \\ 7 & Other oilseeds (exc.\ peanuts) & 267 & Sunflower seed \\ 7 & Other oilseeds (exc.\ peanuts) & 270 & Rapeseed or colza seed \\ 7 & Other oilseeds (exc.\ peanuts) & 275 & Tung Nuts \\ 7 & Other oilseeds (exc.\ peanuts) & 280 & Safflower seed \\ 7 & Other oilseeds (exc.\ peanuts) & 289 & Sesame seed \\ 7 & Other oilseeds (exc.\ peanuts) & 292 & Mustard seed \\ 7 & Other oilseeds (exc.\ peanuts) & 296 & Poppy seed \\ 7 & Other oilseeds (exc.\ peanuts) & 299 & Melonseed \\ 7 & Other oilseeds (exc.\ peanuts) & 310 & Kapok fruit \\ 7 & Other oilseeds (exc.\ peanuts) & 311 & Kapokseed in shell \\ 7 & Other oilseeds (exc.\ peanuts) & 312 & Kapokseed, shelled \\ 7 & Other oilseeds (exc.\ peanuts) & 328 & Seed Cotton \\ 7 & Other oilseeds (exc.\ peanuts) & 329 & Cottonseed \\ 7 & Other oilseeds (exc.\ peanuts) & 333 & Linseed \\ 7 & Other oilseeds (exc.\ peanuts) & 336 & Hempseed \\ 7 & Other oilseeds (exc.\ peanuts) & 339 & Oilseeds nes \\ 8 & Animal feed ingredients \& pet foods & 169 & Beet Pulp \\ 8 & Animal feed ingredients \& pet foods & 628 & Pulp, Waste of Fruit for Feed \\ 8 & Animal feed ingredients \& pet foods & 630 & Cane Tops \\ 8 & Animal feed ingredients \& pet foods & 635 & Straw \& Husks \\ 8 & Animal feed ingredients \& pet foods & 639 & Grasses nes for forage \\ 8 & Animal feed ingredients \& pet foods & 640 & Clover for forage \\ 8 & Animal feed ingredients \& pet foods & 643 & Legumes for silage \\ 8 & Animal feed ingredients \& pet foods & 646 & Turnips for fodder \\ 8 & Animal feed ingredients \& pet foods & 651 & Forage Products nes \\ 8 & Animal feed ingredients \& pet foods & 652 & Vegetable Products for Feed nes \\ 8 & Animal feed ingredients \& pet foods & 846 & Gluten Feed \& Meal \\ 8 & Animal feed ingredients \& pet foods & 858 & Hay (Clover, Lucerne, etc.) \\ 8 & Animal feed ingredients \& pet foods & 859 & Hay nes \\ 8 & Animal feed ingredients \& pet foods & 862 & Alfalfa Meal \& Pellets \\ 9 & Raw \& refined sugar \& sugar crops & 156 & Sugar cane \\ 9 & Raw \& refined sugar \& sugar crops & 157 & Sugar beet \\ 10 & Other sweeteners & 161 & Sugar crops nes \\ 10 & Other sweeteners & 1182 & Honey \\ 11 & Pulses \& legumes(dried, preserved) & 176 & Beans, dry \\ 11 & Pulses \& legumes(dried, preserved) & 181 & Broad beans, dry \\ 11 & Pulses \& legumes(dried, preserved) & 187 & Peas, dry \\ 11 & Pulses \& legumes(dried, preserved) & 191 & Chick-peas, dry \\ 11 & Pulses \& legumes(dried, preserved) & 195 & Cow peas, dry \\ 11 & Pulses \& legumes(dried, preserved) & 197 & Pigeon peas \\ 11 & Pulses \& legumes(dried, preserved) & 201 & Lentils, dry \\ 11 & Pulses \& legumes(dried, preserved) & 203 & Bambara beans \\ 11 & Pulses \& legumes(dried, preserved) & 205 & Vetches \\ 11 & Pulses \& legumes(dried, preserved) & 210 & Lupins \\ 11 & Pulses \& legumes(dried, preserved) & 211 & Pulses nes \\ 12 & Fresh fruit & 486 & Bananas \\ 12 & Fresh fruit & 489 & Plantains \\ 12 & Fresh fruit & 490 & Oranges \\ 12 & Fresh fruit & 495 & Tangerines, mandarins, clementines, satsumas \\ 12 & Fresh fruit & 497 & Lemons \& limes \\ 12 & Fresh fruit & 507 & Grapefruit \& pomelo \\ 12 & Fresh fruit & 512 & Citrus fruit nes \\ 12 & Fresh fruit & 515 & Apples \\ 12 & Fresh fruit & 521 & Pears \\ 12 & Fresh fruit & 523 & Quinces \\ 12 & Fresh fruit & 526 & Apricots \\ 12 & Fresh fruit & 530 & Sour cherries \\ 12 & Fresh fruit & 531 & Cherries \\ 12 & Fresh fruit & 534 & Peaches \& nectarines \\ 12 & Fresh fruit & 536 & Plums \\ 12 & Fresh fruit & 541 & Stone fruit, fresh nes \\ 12 & Fresh fruit & 542 & Pome fruit nes \\ 12 & Fresh fruit & 544 & Strawberries \\ 12 & Fresh fruit & 547 & Raspberries \\ 12 & Fresh fruit & 549 & Gooseberries \\ 12 & Fresh fruit & 550 & Currants \\ 12 & Fresh fruit & 552 & Blueberries \\ 12 & Fresh fruit & 554 & Cranberries \\ 12 & Fresh fruit & 558 & Berries nes \\ 12 & Fresh fruit & 560 & Grapes \\ 12 & Fresh fruit & 561 & Raisins \\ 12 & Fresh fruit & 567 & Watermelons \\ 12 & Fresh fruit & 568 & Melons, Cantaloupes \\ 12 & Fresh fruit & 569 & Figs \\ 12 & Fresh fruit & 571 & Mangoes \\ 12 & Fresh fruit & 572 & Avocados \\ 12 & Fresh fruit & 574 & Pineapples \\ 12 & Fresh fruit & 577 & Dates \\ 12 & Fresh fruit & 587 & Persimmons \\ 12 & Fresh fruit & 591 & Cashewapple \\ 12 & Fresh fruit & 592 & Kiwi fruit \\ 12 & Fresh fruit & 600 & Papayas \\ 12 & Fresh fruit & 603 & Fruit, tropical (fresh) nes \\ 12 & Fresh fruit & 619 & Fruit, fresh nes \\ 13 & Fresh vegetables & 116 & Potatoes \\ 13 & Fresh vegetables & 122 & Sweet potatoes \\ 13 & Fresh vegetables & 125 & Cassava \\ 13 & Fresh vegetables & 135 & Yautia (Cocoyam) \\ 13 & Fresh vegetables & 136 & Taro (Cocoyam) \\ 13 & Fresh vegetables & 137 & Yams \\ 13 & Fresh vegetables & 149 & Roots \& tubers nes \\ 13 & Fresh vegetables & 260 & Olives \\ 13 & Fresh vegetables & 358 & Cabbages \\ 13 & Fresh vegetables & 366 & Artichokes \\ 13 & Fresh vegetables & 367 & Asparagus \\ 13 & Fresh vegetables & 372 & Lettuce \& chicory \\ 13 & Fresh vegetables & 373 & Spinach \\ 13 & Fresh vegetables & 388 & Tomatoes, fresh \\ 13 & Fresh vegetables & 393 & Cauliflowers \& broccoli \\ 13 & Fresh vegetables & 394 & Pumpkins, squash \& gourds \\ 13 & Fresh vegetables & 397 & Cucumbers \& gherkins \\ 13 & Fresh vegetables & 399 & Eggplants \\ 13 & Fresh vegetables & 401 & Chillies \& peppers (green) \\ 13 & Fresh vegetables & 402 & Onions, shallots (green) \\ 13 & Fresh vegetables & 403 & Onions, dry \\ 13 & Fresh vegetables & 406 & Garlic \\ 13 & Fresh vegetables & 407 & Leeks \& other alliaceous vegetables \\ 13 & Fresh vegetables & 414 & Beans, green \\ 13 & Fresh vegetables & 417 & Peas, green \\ 13 & Fresh vegetables & 420 & Broad Beans, Green \\ 13 & Fresh vegetables & 423 & String Beans \\ 13 & Fresh vegetables & 426 & Carrot \\ 13 & Fresh vegetables & 430 & Okra \\ 13 & Fresh vegetables & 446 & Green Corn (Maize) \\ 13 & Fresh vegetables & 449 & Mushrooms \\ 13 & Fresh vegetables & 459 & Chicory roots \\ 13 & Fresh vegetables & 463 & Vegetables, Fresh n.e.s. \\ 14 & Prepared fruits, fruit juices & 527 & Apricots, Dried \\ 14 & Prepared fruits, fruit juices & 537 & Plums, dried \\ 14 & Prepared fruits, fruit juices & 570 & Figs, Dried \\ 14 & Prepared fruits, fruit juices & 620 & Fruit, dried nes \\ 15 & Prepared vegetables & 120 & Potato Offals \\ 15 & Prepared vegetables & 128 & Cassava, Dried \\ 16 & Nuts & 216 & Brazil nuts \\ 16 & Nuts & 217 & Cashew nuts \\ 16 & Nuts & 220 & Chestnuts \\ 16 & Nuts & 221 & Almonds \\ 16 & Nuts & 222 & Walnuts \\ 16 & Nuts & 223 & Pistachios \\ 16 & Nuts & 224 & Kolanuts \\ 16 & Nuts & 225 & Hazelnuts (Filberts) \\ 16 & Nuts & 226 & Areca nuts \\ 16 & Nuts & 229 & Brazil Nuts, Shelled \\ 16 & Nuts & 230 & Cashew Nuts, Shelled \\ 16 & Nuts & 231 & Almonds, Shelled \\ 16 & Nuts & 232 & Walnuts, Shelled \\ 16 & Nuts & 233 & Hazelnuts, Shelled \\ 16 & Nuts & 234 & Nuts nes \\ 17 & Live Cattle & 866 & Cattle \\ 17 & Live Cattle & 946 & Buffaloes \\ 18 & Live Swine & 1034 & Pigs \\ 19 & Eggs & 1062 & Hen eggs \\ 19 & Eggs & 1091 & Eggs, exc.\ hen eggs \\ 20 & Other meats, livest.\ pr.\, live animals & 976 & Sheep \\ 20 & Other meats, livest.\ pr.\, live animals & 987 & Wool, Greasy \\ 20 & Other meats, livest.\ pr.\, live animals & 1009 & Wool, Hair Waste \\ 20 & Other meats, livest.\ pr.\, live animals & 1016 & Goats \\ 20 & Other meats, livest.\ pr.\, live animals & 1026 & Skins, Wet-Salted (Goats) \\ 20 & Other meats, livest.\ pr.\, live animals & 1031 & Coarse goat hair \\ 20 & Other meats, livest.\ pr.\, live animals & 1057 & Chickens \\ 20 & Other meats, livest.\ pr.\, live animals & 1068 & Ducks \\ 20 & Other meats, livest.\ pr.\, live animals & 1079 & Turkeys \\ 20 & Other meats, livest.\ pr.\, live animals & 1083 & Pigeons and other birds \\ 20 & Other meats, livest.\ pr.\, live animals & 1096 & Horses \\ 20 & Other meats, livest.\ pr.\, live animals & 1107 & Asses \\ 20 & Other meats, livest.\ pr.\, live animals & 1110 & Mules \\ 20 & Other meats, livest.\ pr.\, live animals & 1126 & Camels \\ 20 & Other meats, livest.\ pr.\, live animals & 1134 & Hides, Wet-Salted (Camels) \\ 20 & Other meats, livest.\ pr.\, live animals & 1136 & Hides nes, Camels \\ 20 & Other meats, livest.\ pr.\, live animals & 1140 & Rabbits \\ 20 & Other meats, livest.\ pr.\, live animals & 1150 & Other rodents \\ 20 & Other meats, livest.\ pr.\, live animals & 1157 & Other camelids \\ 20 & Other meats, livest.\ pr.\, live animals & 1169 & Live animals, non food nes \\ 20 & Other meats, livest.\ pr.\, live animals & 1171 & Live animals nes \\ 20 & Other meats, livest.\ pr.\, live animals & 1181 & Bees \\ 20 & Other meats, livest.\ pr.\, live animals & 1183 & Beeswax \\ 20 & Other meats, livest.\ pr.\, live animals & 1185 & Cocoons, reelable \\ 20 & Other meats, livest.\ pr.\, live animals & 1216 & Hides nes \\ 20 & Other meats, livest.\ pr.\, live animals & 1218 & Hair, fine \\ 21 & Cocoa and cocoa products & 661 & Cocoa beans \\ 22 & Beverages, nec & 656 & Coffee green \\ 22 & Beverages, nec & 667 & Tea \\ 22 & Beverages, nec & 671 & Mate \\ 23 & Cotton & 767 & Cotton Lint \\ 23 & Cotton & 769 & Cotton Waste \\ 24 & Tobacco leaves \& cigarettes & 826 & Tobacco leaves \\ 25 & Spices & 687 & Pepper \\ 25 & Spices & 689 & Pimento \\ 25 & Spices & 692 & Vanilla \\ 25 & Spices & 693 & Cinnamon (canella) \\ 25 & Spices & 698 & Cloves \\ 25 & Spices & 702 & Nutmeg, mace, cardamoms \\ 25 & Spices & 711 & Anise, badian, fennel \\ 25 & Spices & 720 & Ginger \\ 25 & Spices & 723 & Spices nes \\ 26 & Other ag.\ products, nec & 460 & Vegetable products, fresh or dry nes \\ 26 & Other ag.\ products, nec & 461 & Carobs \\ 26 & Other ag.\ products, nec & 654 & Dregs from brewing, distillation \\ 26 & Other ag.\ products, nec & 677 & Hops \\ 26 & Other ag.\ products, nec & 748 & Peppermint, Spearmint \\ 26 & Other ag.\ products, nec & 754 & Pyrethrum, dried flowers \\ 26 & Other ag.\ products, nec & 755 & Pyrethrum Extract \\ 26 & Other ag.\ products, nec & 771 & Flax, raw or retted \\ 26 & Other ag.\ products, nec & 777 & Hemp fibre and tow \\ 26 & Other ag.\ products, nec & 778 & Kapok fibre \\ 26 & Other ag.\ products, nec & 780 & Jute \\ 26 & Other ag.\ products, nec & 782 & Jute-like fibres \\ 26 & Other ag.\ products, nec & 788 & Ramie \\ 26 & Other ag.\ products, nec & 789 & Sisal \\ 26 & Other ag.\ products, nec & 800 & Agave fibres nes \\ 26 & Other ag.\ products, nec & 809 & Abaca manila hemp \\ 26 & Other ag.\ products, nec & 813 & Coir \\ 26 & Other ag.\ products, nec & 821 & Fibre crops nes \\ 26 & Other ag.\ products, nec & 836 & Natural rubber \\ 26 & Other ag.\ products, nec & 837 & Rubber, Natural (Dry) \\ 26 & Other ag.\ products, nec & 839 & Natural gums \\ 26 & Other ag.\ products, nec & 1293 & Crude Organic Materials nes \\ \hline \hline \multicolumn{4}{p{0.85\linewidth}}{\scriptsize\textbf{Notes}: This table presents the concordance that we created between the ITPD-E agriculture classification and the FCL classification.} \end{longtable}} \clearpage \begin{sidewaystable}[htbp]\scriptsize \caption{Mining: ITPD-E-R02 Classification and Concordances\label{tab:ITPD-E_class_mining}}\centering\medskip \begin{tabular}{clclcl}\hline\hline ITPD-E-R02 Code & ITPD-E-R02 Description & ISIC3 & ISIC rev.\ 3 Description & ISIC4 & ISIC rev.\ 4 Description \\\hline 29 & Mining of hard coal & 101 & Mining and agglomeration of hard coal & 51 & Mining of hard coal \\ 30 & Mining of lignite & 102 & Mining and agglomeration of lignite & 52 & Mining of lignite \\ 31 & Extraction crude oil and gas & 111 & Extraction crude oil and gas & 6 & Extraction of crude oil and gas \\ 32 & Mining of iron ores & 131 & Iron ores & 71 & Mining of iron ores \\ 33 & Other mining and quarring & 190 & C-(101+102+111+131) & 90 & B-(051+052+61+62+071) \\ 34 & Electricity prodcn, collcn, and distr. & 401 & Electricity prodcn, collcn, and distr. & 351 & Electric power generation, transmission \\ 35 & Gas production and distribution & 402 & Gas production and distribution & 352 & Manufacture of gas \\ \hline \hline \multicolumn{6}{p{0.95\linewidth}}{\scriptsize\textbf{Notes}: This table presents the concordance that we created between the ITPD-E-R02 mining classification, the ISIC rev.\ 3 and ISIC rev.\ 4 classifications. The concordances are the same as in ITPD-E but the ITPD-E-R02 classification is shifted up by two numbers due to the introduction of industry `27 Forestry' and `28 Fishing'.} \end{tabular} \end{sidewaystable} \clearpage {\tiny\singlespacing \begin{longtable}{c l c c} \caption{ \label{tab:ITPD-E_class_manuf} Manufacturing: ITPD-E-R02 Classification and Concordances}\\ \hline\hline ITPD-E-R02 Code & ITPD-E-R02 Description & ISIC3 & ISIC4 \\\hline \endfirsthead \hline ITPD-E-R02 Code & ITPD-E-R02 Description & ISIC3 & ISIC4 \\\hline \endhead \hline \multicolumn{4}{r}{{Continued on next page}}\\ \endfoot \endlastfoot 36 & Processing/preserving of meat & 1511 & 1010 \\ 37 & Processing/preserving of fish & 1512 & 1020 \\ 38 & Processing/preserving of fruit \& vegetables & 1513 & 1030 \\ 39 & Vegetable and animal oils and fats & 1514 & 1040 \\ 40 & Dairy products & 1520 & 1050 \\ 41 & Grain mill products & 1531 & 1061 \\ 42 & Starches and starch products & 1532 & 1062 \\ 43 & Prepared animal feeds & 1533 & 1080 \\ 44 & Bakery products & 1541 & 1071 \\ 45 & Sugar & 1542 & 1072 \\ 46 & Cocoa chocolate and sugar confectionery & 1543 & 1073 \\ 47 & Macaroni noodles \& similar products & 1544 & 1074 \\ 48 & Other food products n.e.c. & 1549 & 1075+1079 \\ 49 & Distilling rectifying \& blending of spirits & 1551 & 1101 \\ 50 & Wines & 1552 & 1102 \\ 51 & Malt liquors and malt & 1553 & 1103 \\ 52 & Soft drinks; mineral waters & 1554 & 1104 \\ 53 & Tobacco products & 1600 & 1200 \\ 54 & Textile fibre preparation; textile weaving & 1711 & 1311+1312 \\ 55 & Made-up textile articles except apparel & 1721 & 1392 \\ 56 & Carpets and rugs & 1722 & 1393 \\ 57 & Cordage rope twine and netting & 1723 & 1394 \\ 58 & Other textiles n.e.c. & 1729 & 1399 \\ 59 & Knitted and crocheted fabrics and articles & 1730 & 1430+1391 \\ 60 & Wearing apparel except fur apparel & 1810 & 1410 \\ 61 & Dressing \& dyeing of fur; processing of fur & 1820 & 1420 \\ 62 & Tanning and dressing of leather & 1911 & 1511 \\ 63 & Luggage handbags etc.; saddlery \& harness & 1912 & 1512 \\ 64 & Footwear & 1920 & 1520 \\ 65 & Sawmilling and planing of wood & 2010 & 1610 \\ 66 & Veneer sheets plywood particle board etc. & 2021 & 1621 \\ 67 & Builders' carpentry and joinery & 2022 & 1622 \\ 68 & Wooden containers & 2023 & 1623 \\ 69 & Other wood products; articles of cork/straw & 2029 & 1629 \\ 70 & Pulp paper and paperboard & 2101 & 1701 \\ 71 & Corrugated paper and paperboard & 2102 & 1702 \\ 72 & Other articles of paper and paperboard & 2109 & 1709 \\ 73 & Publishing of books and other publications & 2211 & \\ 74 & Publishing of newspapers journals etc. & 2212 & \\ 75 & Publishing of recorded media & 2213 & \\ 76 & Other publishing & 2219 & \\ 77 & Printing & 2221 & 1811 \\ 78 & Service activities related to printing & 2222 & 1812 \\ %77 & Reproduction of recorded media & 2230 & 1820 \\ 79 & Coke oven products & 2310 & 1910 \\ 80 & Refined petroleum products & 2320 & 1920 \\ 81 & Processing of nuclear fuel & 2330 & \\ 82 & Basic chemicals except fertilizers & 2411 & 2011 \\ 83 & Fertilizers and nitrogen compounds & 2412 & 2012 \\ 84 & Plastics in primary forms; synthetic rubber & 2413 & 2013 \\ 85 & Pesticides and other agro-chemical products & 2421 & 2021 \\ 86 & Paints varnishes printing ink and mastics & 2422 & 2022 \\ 87 & Pharmaceuticals medicinal chemicals etc. & 2423 & 2100 \\ 88 & Soap cleaning \& cosmetic preparations & 2424 & 2023 \\ 89 & Other chemical products n.e.c. & 2429 & 2029+2680 \\ 90 & Man-made fibers & 2430 & 2030 \\ 91 & Rubber tires and tubes & 2511 & 2211 \\ 92 & Other rubber products & 2519 & 2219 \\ 93 & Plastic products & 2520 & 2220 \\ 94 & Glass and glass products & 2610 & 2310 \\ 95 & Pottery china and earthenware & 2691 & 2393 \\ 96 & Refractory ceramic products & 2692 & 2391 \\ 97 & Struct.non-refractory clay; ceramic products & 2693 & 2392 \\ 98 & Cement lime and plaster & 2694 & 2394 \\ 99 & Articles of concrete cement and plaster & 2695 & 2395 \\ 100 & Cutting shaping \& finishing of stone & 2696 & 2396 \\ 101 & Other non-metallic mineral products n.e.c. & 2699 & 2399 \\ 102 & Basic iron and steel & 2710 & 2410 \\ 103 & Basic precious and non-ferrous metals & 2720 & 2420 \\ %103 & Casting of iron and steel & 2731 & 2431 \\ 104 & Structural metal products & 2811 & 2511 \\ 105 & Tanks reservoirs and containers of metal & 2812 & 2512 \\ 106 & Steam generators & 2813 & 2513 \\ 107 & Cutlery hand tools and general hardware & 2893 & 2593 \\ 108 & Other fabricated metal products n.e.c. & 2899 & 2599 \\ 109 & Engines \& turbines (not for transport equipment) & 2911 & 2811 \\ 110 & Pumps compressors taps and valves & 2912 & 2812+2813 \\ 111 & Bearings gears gearing \& driving elements & 2913 & 2814 \\ 112 & Ovens furnaces and furnace burners & 2914 & 2815 \\ 113 & Lifting and handling equipment & 2915 & 2816 \\ 114 & Other general purpose machinery & 2919 & 2819 \\ 115 & Agricultural and forestry machinery & 2921 & 2821 \\ 116 & Machine tools & 2922 & 2818+2822 \\ 117 & Machinery for metallurgy & 2923 & 2823 \\ 118 & Machinery for mining \& construction & 2924 & 2824 \\ 119 & Food/beverage/tobacco processing machinery & 2925 & 2825 \\ 120 & Machinery for textile apparel and leather & 2926 & 2826 \\ 121 & Weapons and ammunition & 2927 & 2520+3040 \\ 122 & Other special purpose machinery & 2929 & 2829 \\ 123 & Domestic appliances n.e.c. & 2930 & 2750 \\ 124 & Office accounting and computing machinery & 3000 & 2620+2817 \\ 125 & Electric motors generators and transformers & 3110 & 2710 \\ 126 & Electricity distribution \& control apparatus & 3120 & 2733 \\ 127 & Insulated wire and cable & 3130 & 2731+2732 \\ 128 & Accumulators primary cells and batteries & 3140 & 2720 \\ 129 & Lighting equipment and electric lamps & 3150 & 2740 \\ 130 & Other electrical equipment n.e.c. & 3190 & 2790 \\ 131 & Electronic valves tubes etc. & 3210 & 2610 \\ 132 & TV/radio transmitters; line comm. apparatus & 3220 & 2630 \\ 133 & TV and radio receivers and associated goods & 3230 & 2640 \\ 134 & Medical surgical and orthopedic equipment & 3311 & 2660+3250 \\ 135 & Measuring/testing/navigating appliances and equipment & 3312+3313 & 2651 \\ 136 & Optical instruments \& photographic equipment & 3320 & 2670 \\ 137 & Watches and clocks & 3330 & 2652 \\ 138 & Motor vehicles & 3410 & 2910 \\ 139 & Automobile bodies trailers \& semi-trailers & 3420 & 2920 \\ 140 & Parts/accessories for automobiles & 3430 & 2930 \\ 141 & Building and repairing of ships & 3511 & 3011 \\ 142 & Building/repairing of pleasure/sport. boats & 3512 & 3012 \\ 143 & Railway/tramway locomotives \& rolling stock & 3520 & 3020 \\ 144 & Aircraft and spacecraft & 3530 & 3030 \\ 145 & Motorcycles & 3591 & 3091 \\ 146 & Bicycles and invalid carriages & 3592 & 3092 \\ 147 & Other transport equipment n.e.c. & 3599 & 3099 \\ 148 & Furniture & 3610 & 3100 \\ 149 & Jewelery and related articles & 3691 & 3211+3212 \\ 150 & Musical instruments & 3692 & 3220 \\ 151 & Sports goods & 3693 & 3230 \\ 152 & Games and toys & 3694 & 3240 \\ 153 & Other manufacturing n.e.c. & 3699 & 3290 \\ \hline\hline \multicolumn{4}{p{0.75\linewidth}}{\scriptsize\textbf{Notes}: This table presents the concordance that we created between the ITPD-E-R02 manufacturing classification, the ISIC rev.\ 3 and ISIC rev.\ 4 classifications. The difference between this classification and the classification in ITPD-E is that the industries `Reproduction of recorded media' and `Casting of iron and steel' are not in ITPD-E-R02.} \end{longtable}} \clearpage \begin{sidewaystable}[htbp] \begin{threeparttable} \caption{\label{tab:ITPD-E_class_services} Services: EBOPS--ISIC--ITPD Concordance}\centering\medskip\small \begin{tabular}{lllll}\hline\hline ITPD-E Code & ITPD-E Description & EBOPS 2002 & EBOPS 2010 & ISIC Rev. 4 \\ \hline 154 & Manufacturing services on physical inputs owned by others & & SA & -- \\ 155 & Maintenance and repair services n.i.e. & & SB & -- \\ 156 & Transport & 205, 246 & SC & H \\ 157 & Travel & 237, 243 & SDA + SDB3 & I \\ 158 & Construction & 249 & SE & F \\ 159 & Insurance and pension services & 253 & SF & K (60\%) \\ 160 & Financial services & 260 & SG & K (40\%) \\ 161 & Charges for the use of intellectual property n.i.e. & 266 & SH & -- \\ 162 & Telecommunications, computer, and information services & 247, 262, 288 & SI + SK1 & J \\ 163 & Other business services & 272, 273 & SJ excl SJ34 & M + N \\ 164 & Heritage and recreational services & -- & SK23\tnote{a} & R \\ 165 & Health services & 241, 896 & SDB1 + SK21 & Q \\ 166 & Education services & 242, 895 & SDB2 + SK22 & P \\ 167 & Government goods and services n.i.e. & 291 & SL & -- \\ 168 & Services not allocated & 982 & SN & -- \\ 169 & Trade-related services & 271 & SJ34 & G \\ 170 & Other personal services & -- & SK24\tnote{a} & S \\ \hline\hline \end{tabular} \begin{tablenotes}{ \item[a] EBOPS codes SK23 and SK24 are new to BPM6 and have no backwards correspondence in BPM5.\\ The concordance in this table differs from \cite[Table 14]{Wettsteinetal2019} in three respects: \item[(1)] ISIC industry L is not concorded to `other business services' (EBOPS SJ); \item[(2)] Rather than aggregating financial services and insurance services, respectively, we keep these two services products separate and split ISIC category K according to a fixed fraction; \item[(3)] We do not include EBOPS SW (trade margins of wholesalers and retailers) as part of SJ34 because this code is not included in the WTO-UNCTAD-ITC annual trade in services dataset.} \end{tablenotes} \end{threeparttable} \end{sidewaystable} \begin{table}[htbp] \centering \caption{Comparison of the Total Number of Observations} \label{tab:compare_totals} \begin{tabular}{lr} \hline \hline {} & Number of observations \\ \midrule In release R1 & 38,518,253 \\ In release R2 & 72,534,869 \\ In either release & 73,510,718 \\ In both releases & 37,542,404 \\ In R1, but not in R2 & 975,849 \\ In R2, but not in R1 & 34,992,465 \\ \hline \hline \end{tabular} \end{table} \begin{table}[htbp] \centering \singlespacing \caption{Comparison of Number and Value of Trade Flows, By Year} \label{tab:compare_by_year} \centering \begin{tabular}{lrrrr} \hline \hline & \multicolumn{2}{c}{ITPD-E R01} & \multicolumn{2}{c}{ITPD-E R02} \\ Year & Freq & Value & Freq & Value \\ \hline 1986 & & & 120,430 & 105 \\ 1987 & & & 121,728 & 111 \\ 1988 & & & 1,129,339 & 1,306 \\ 1989 & & & 1,298,872 & 1,935 \\ 1990 & & & 1,367,742 & 3,138 \\ 1991 & & & 1,473,637 & 4,349 \\ 1992 & & & 1,837,326 & 5,357 \\ 1993 & & & 2,004,519 & 5,973 \\ 1994 & & & 2,075,523 & 9,325 \\ 1995 & & & 2,110,024 & 11,668 \\ 1996 & & & 2,115,491 & 12,848 \\ 1997 & & & 2,164,968 & 15,979 \\ 1998 & & & 2,189,455 & 15,730 \\ 1999 & & & 2,229,839 & 16,295 \\ 2000 & 2,213,278 & 43,327 & 2,448,006 & 43,281 \\ 2001 & 2,218,685 & 42,580 & 2,454,598 & 42,612 \\ 2002 & 2,230,848 & 44,222 & 2,467,250 & 44,058 \\ 2003 & 2,252,326 & 51,582 & 2,485,058 & 51,182 \\ 2004 & 2,258,436 & 60,130 & 2,490,433 & 59,645 \\ 2005 & 2,264,393 & 65,113 & 2,501,253 & 64,997 \\ 2006 & 2,289,096 & 71,416 & 2,533,745 & 71,720 \\ 2007 & 2,292,213 & 81,824 & 2,539,988 & 81,015 \\ 2008 & 2,291,181 & 89,455 & 2,539,993 & 89,014 \\ 2009 & 2,287,047 & 76,832 & 2,539,544 & 79,507 \\ 2010 & 2,285,389 & 83,995 & 2,542,579 & 86,725 \\ 2011 & 2,281,534 & 93,723 & 2,542,149 & 99,624 \\ 2012 & 2,282,782 & 84,572 & 2,542,748 & 101,527 \\ 2013 & 2,277,242 & 84,394 & 2,536,653 & 104,529 \\ 2014 & 2,268,835 & 79,795 & 2,527,113 & 105,075 \\ 2015 & 2,264,521 & 66,512 & 2,525,834 & 97,388 \\ 2016 & 2,260,447 & 61,578 & 2,522,556 & 84,414 \\ 2017 & & & 2,522,672 & 88,433 \\ 2018 & & & 2,522,523 & 92,145 \\ 2019 & & & 2,511,281 & 77,553 \\ \bottomrule \hline \hline \multicolumn{5}{l}{Note: `Value' is in billions of USD.} \\ \end{tabular} \end{table} \clearpage \centering \singlespacing \scriptsize \begin{longtable}{lllrrrr} \caption{Comparison of Number and Value of Trade Flows, By Industry} \label{tab:compare_by_industry}\\ \hline \hline \multicolumn{2}{c}{Industry ID} & & \multicolumn{2}{c}{ITPD-E R01} & \multicolumn{2}{c}{ITPD-E R02} \\ R01 & R02 & Industry Description & \multicolumn{1}{c}{Freq} & \multicolumn{1}{c}{Value} & \multicolumn{1}{c}{Freq} & \multicolumn{1}{c}{Value} \\ \hline \endfirsthead \hline \multicolumn{2}{c}{Industry ID} & & \multicolumn{2}{c}{ITPD-E R01} & \multicolumn{2}{c}{ITPD-E R02} \\ R01 & R02 & Industry Description & \multicolumn{1}{c}{Freq} & \multicolumn{1}{c}{Value} & \multicolumn{1}{c}{Freq} & \multicolumn{1}{c}{Value} \\ \hline \endhead \hline \multicolumn{7}{r}{{Continued on next page}}\\ \endfoot \endlastfoot 1 & 1 & Wheat & 77,845 & 2,319 & 161,462 & 3,598 \\ 2 & 2 & Rice (raw) & 63,997 & 3,864 & 264,780 & 6,290 \\ 3 & 3 & Corn & 87,885 & 2,704 & 190,760 & 4,374 \\ 4 & 4 & Other cereals & 81,678 & 927 & 176,680 & 1,452 \\ 5 & 5 & Cereal products & 39,654 & 15 & 82,098 & 24 \\ 6 & 6 & Soybeans & 55,957 & 1,339 & 113,761 & 2,248 \\ 7 & 7 & Other oilseeds (excluding peanuts) & 160,283 & 2,713 & 344,260 & 3,721 \\ 8 & 8 & Animal feed ingredients and pet foods & 71,448 & 78 & 264,382 & 343 \\ 9 & 9 & Raw and refined sugar and sugar crops & 10,651 & 1,071 & 21,611 & 1,599 \\ 10 & 10 & Other sweeteners & 82,972 & 91 & 174,104 & 133 \\ 11 & 11 & Pulses and legumes, dried, preserved & 134,352 & 533 & 285,160 & 826 \\ 12 & 12 & Fresh fruit & 211,150 & 5,831 & 450,335 & 8,532 \\ 13 & 13 & Fresh vegetables & 175,575 & 8,722 & 373,785 & 12,562 \\ 14 & 14 & Prepared fruits and fruit juices & 106,861 & 32 & 216,489 & 48 \\ 15 & 15 & Prepared vegetables & 16,594 & 21 & 37,767 & 39 \\ 16 & 16 & Nuts & 127,163 & 648 & 265,904 & 961 \\ 17 & 17 & Live Cattle & 31,588 & 108 & 73,982 & 192 \\ 18 & 18 & Live Swine & 16,511 & 53 & 35,096 & 81 \\ 19 & 19 & Eggs & 65,981 & 1,596 & 147,396 & 2,443 \\ 20 & 20 & Other meats, livestock products, and live animals & 173,954 & 265 & 402,403 & 575 \\ 21 & 21 & Cocoa and cocoa products & 38,609 & 138 & 89,594 & 213 \\ 22 & 22 & Beverages, nec & 192,290 & 478 & 404,965 & 795 \\ 23 & 23 & Cotton & 99,474 & 746 & 226,642 & 383 \\ 24 & 24 & Tobacco leaves and cigarettes & 104,397 & 295 & 229,436 & 490 \\ 25 & 25 & Spices & 186,919 & 214 & 396,341 & 334 \\ 26 & 26 & Other agricultural products, nec & 271,908 & 1,049 & 559,554 & 1,588 \\ & 27 & Forestry & & & 474,015 & 558 \\ & 28 & Fishing & & & 391,607 & 376 \\ 27 & 29 & Mining of hard coal & 75,090 & 3,318 & 136,108 & 5,834 \\ 28 & 30 & Mining of lignite & 19,707 & 185 & 38,152 & 401 \\ 29 & 31 & Extraction crude petroleum and natural gas & 92,441 & 23,781 & 172,182 & 37,881 \\ 30 & 32 & Mining of iron ores & 45,156 & 2,083 & 82,390 & 3,020 \\ 31 & 33 & Other mining and quarring & 306,736 & 5,869 & 588,170 & 20,624 \\ 32 & 34 & Electricity production, collection, and distribution & 21,438 & 13,884 & 36,842 & 24,798 \\ 33 & 35 & Gas production and distribution & 17,634 & 2,054 & 17,305 & 3,863 \\ 34 & 36 & Processing/preserving of meat & 264,080 & 9,208 & 516,818 & 14,567 \\ 35 & 37 & Processing/preserving of fish & 304,756 & 2,268 & 595,490 & 3,812 \\ 36 & 38 & Processing/preserving of fruit \& vegetables & 333,462 & 2,458 & 632,741 & 4,865 \\ 37 & 39 & Vegetable and animal oils and fats & 266,236 & 3,605 & 518,023 & 6,130 \\ 38 & 40 & Dairy products & 253,217 & 4,931 & 475,034 & 9,373 \\ 39 & 41 & Grain mill products & 270,470 & 2,233 & 515,338 & 4,283 \\ 40 & 42 & Starches and starch products & 183,214 & 586 & 343,283 & 1,073 \\ 41 & 43 & Prepared animal feeds & 169,836 & 2,384 & 325,852 & 4,835 \\ 42 & 44 & Bakery products & 252,274 & 3,072 & 473,776 & 5,642 \\ 43 & 45 & Sugar & 188,988 & 1,137 & 363,745 & 1,874 \\ 44 & 46 & Cocoa chocolate and sugar confectionery & 280,421 & 1,613 & 530,735 & 2,700 \\ 45 & 47 & Macaroni noodles \& similar products & 184,870 & 547 & 347,555 & 1,019 \\ 46 & 48 & Other food products n.e.c. & 374,789 & 4,113 & 702,654 & 7,786 \\ 47 & 49 & Distilling rectifying \& blending of spirits & 246,847 & 1,619 & 474,545 & 2,139 \\ 48 & 50 & Wines & 213,716 & 845 & 400,350 & 1,397 \\ 49 & 51 & Malt liquors and malt & 179,923 & 1,440 & 342,300 & 2,645 \\ 50 & 52 & Soft drinks; mineral waters & 257,976 & 2,079 & 475,168 & 3,758 \\ 51 & 53 & Tobacco products & 235,124 & 2,633 & 409,339 & 5,320 \\ 52 & 54 & Textile fibre preparation; textile weaving & 344,835 & 3,705 & 664,162 & 7,257 \\ 53 & 55 & Made-up textile articles except apparel & 391,348 & 1,263 & 739,452 & 1,876 \\ 54 & 56 & Carpets and rugs & 265,513 & 422 & 511,303 & 798 \\ 55 & 57 & Cordage rope twine and netting & 234,543 & 105 & 438,109 & 195 \\ 56 & 58 & Other textiles n.e.c. & 307,153 & 1,001 & 575,255 & 1,677 \\ 57 & 59 & Knitted and crocheted fabrics and articles & 397,698 & 2,098 & 704,883 & 3,165 \\ 58 & 60 & Wearing apparel except fur apparel & 506,144 & 6,163 & 940,066 & 9,986 \\ 59 & 61 & Dressing \& dyeing of fur; processing of fur & 130,653 & 92 & 248,006 & 164 \\ 60 & 62 & Tanning and dressing of leather & 184,452 & 578 & 333,818 & 981 \\ 61 & 63 & Luggage handbags etc.; saddlery \& harness & 366,600 & 838 & 690,464 & 1,258 \\ 62 & 64 & Footwear & 372,876 & 2,129 & 711,001 & 3,448 \\ 63 & 65 & Sawmilling and planing of wood & 247,071 & 2,013 & 457,447 & 3,070 \\ 64 & 66 & Veneer sheets plywood particle board etc. & 224,925 & 1,328 & 428,831 & 2,561 \\ 65 & 67 & Builders' carpentry and joinery & 209,825 & 1,405 & 388,821 & 2,476 \\ 66 & 68 & Wooden containers & 195,088 & 299 & 354,160 & 566 \\ 67 & 69 & Other wood products; articles of cork/straw & 331,583 & 492 & 625,893 & 983 \\ 68 & 70 & Pulp paper and paperboard & 301,621 & 4,696 & 554,714 & 7,845 \\ 69 & 71 & Corrugated paper and paperboard & 283,916 & 2,310 & 525,845 & 4,577 \\ 70 & 72 & Other articles of paper and paperboard & 374,885 & 1,588 & 649,022 & 2,827 \\ 71 & 73 & Publishing of books and other publications & 378,505 & 585 & 707,063 & 1,071 \\ 72 & 74 & Publishing of newspapers journals etc. & 175,255 & 1,008 & 330,423 & 1,729 \\ 73 & 75 & Publishing of recorded media & 169,299 & 189 & 389,849 & 434 \\ 74 & 76 & Other publishing & 330,683 & 198 & 616,388 & 398 \\ 75 & 77 & Printing & 373,622 & 3,522 & 646,272 & 6,568 \\ 76 & 78 & Service activities related to printing & 104,597 & 460 & 195,249 & 762 \\ 77 & & Reproduction of recorded media & 33,613 & 281 & & \\ 78 & 79 & Coke oven products & 53,512 & 6,043 & 102,682 & 1,110 \\ 79 & 80 & Refined petroleum products & 319,655 & 23,889 & 579,355 & 34,644 \\ 80 & 81 & Processing of nuclear fuel & 81,830 & 402 & 149,557 & 427 \\ 81 & 82 & Basic chemicals except fertilizers & 367,995 & 11,724 & 693,409 & 19,195 \\ 82 & 83 & Fertilizers and nitrogen compounds & 197,467 & 2,045 & 380,385 & 3,453 \\ 83 & 84 & Plastics in primary forms; synthetic rubber & 296,165 & 6,266 & 559,196 & 9,989 \\ 84 & 85 & Pesticides and other agro-chemical products & 214,444 & 763 & 408,568 & 1,415 \\ 85 & 86 & Paints varnishes printing ink and mastics & 295,304 & 1,862 & 551,441 & 3,365 \\ 86 & 87 & Pharmaceuticals medicinal chemicals etc. & 380,241 & 11,552 & 717,974 & 19,818 \\ 87 & 88 & Soap cleaning \& cosmetic preparations & 388,759 & 3,344 & 733,862 & 5,932 \\ 88 & 89 & Other chemical products n.e.c. & 435,301 & 4,753 & 780,479 & 8,091 \\ 89 & 90 & Man-made fibres & 187,332 & 1,177 & 347,947 & 2,044 \\ 90 & 91 & Rubber tyres and tubes & 275,980 & 1,765 & 521,156 & 2,931 \\ 91 & 92 & Other rubber products & 389,019 & 1,638 & 722,035 & 2,737 \\ 92 & 93 & Plastic products & 482,105 & 10,319 & 898,032 & 18,673 \\ 93 & 94 & Glass and glass products & 371,857 & 2,961 & 697,158 & 4,028 \\ 94 & 95 & Pottery china and earthenware & 323,151 & 584 & 614,680 & 1,078 \\ 95 & 96 & Refractory ceramic products & 163,078 & 429 & 304,355 & 846 \\ 96 & 97 & Struct.non-refractory clay; ceramic products & 234,859 & 888 & 385,166 & 1,686 \\ 97 & 98 & Cement lime and plaster & 167,892 & 1,887 & 316,025 & 3,245 \\ 98 & 99 & Articles of concrete cement and plaster & 193,650 & 2,788 & 361,036 & 5,530 \\ 99 & 100 & Cutting shaping \& finishing of stone & 198,141 & 618 & 366,762 & 1,067 \\ 100 & 101 & Other non-metallic mineral products n.e.c. & 275,469 & 1,277 & 515,930 & 2,231 \\ 101 & 102 & Basic iron and steel & 375,386 & 18,681 & 692,029 & 28,158 \\ 102 & 103 & Basic precious and non-ferrous metals & 331,416 & 11,638 & 617,097 & 19,968 \\ 103 & & Casting of iron and steel & 264,452 & 1,266 & & \\ 104 & 104 & Structural metal products & 288,356 & 4,509 & 539,604 & 8,431 \\ 105 & 105 & Tanks reservoirs and containers of metal & 223,679 & 786 & 412,513 & 1,369 \\ 106 & 106 & Steam generators & 146,238 & 736 & 272,156 & 1,074 \\ 107 & 107 & Cutlery hand tools and general hardware & 431,422 & 2,009 & 786,787 & 3,312 \\ 108 & 108 & Other fabricated metal products n.e.c. & 483,221 & 5,043 & 894,532 & 9,172 \\ 109 & 109 & Engines \& turbines (not for transport equipment) & 225,913 & 1,966 & 427,948 & 3,278 \\ 110 & 110 & Pumps compressors taps and valves & 409,150 & 3,868 & 774,183 & 5,831 \\ 111 & 111 & Bearings gears gearing \& driving elements & 337,549 & 1,647 & 640,411 & 2,656 \\ 112 & 112 & Ovens furnaces and furnace burners & 197,186 & 285 & 432,717 & 836 \\ 113 & 113 & Lifting and handling equipment & 304,791 & 2,262 & 576,201 & 3,988 \\ 114 & 114 & Other general purpose machinery & 436,553 & 5,288 & 812,989 & 8,229 \\ 115 & 115 & Agricultural and forestry machinery & 248,332 & 1,490 & 464,647 & 2,717 \\ 116 & 116 & Machine tools & 349,097 & 2,385 & 644,355 & 3,915 \\ 117 & 117 & Machinery for metallurgy & 120,723 & 351 & 223,857 & 970 \\ 118 & 118 & Machinery for mining \& construction & 334,163 & 2,710 & 624,198 & 4,938 \\ 119 & 119 & Food/beverage/tobacco processing machinery & 255,581 & 643 & 482,750 & 1,151 \\ 120 & 120 & Machinery for textile apparel and leather & 268,892 & 619 & 508,391 & 1,106 \\ 121 & 121 & Weapons and ammunition & 148,226 & 512 & 281,244 & 802 \\ 122 & 122 & Other special purpose machinery & 371,734 & 4,286 & 682,623 & 7,429 \\ 123 & 123 & Domestic appliances n.e.c. & 367,690 & 3,033 & 695,056 & 5,532 \\ 124 & 124 & Office accounting and computing machinery & 448,807 & 9,571 & 837,300 & 14,533 \\ 125 & 125 & Electric motors generators and transformers & 457,444 & 4,881 & 738,947 & 7,770 \\ 126 & 126 & Electricity distribution \& control apparatus & 407,076 & 3,607 & 755,770 & 5,160 \\ 127 & 127 & Insulated wire and cable & 356,089 & 2,193 & 634,359 & 4,060 \\ 128 & 128 & Accumulators primary cells and batteries & 293,490 & 969 & 535,878 & 1,651 \\ 129 & 129 & Lighting equipment and electric lamps & 373,200 & 1,342 & 664,967 & 2,205 \\ 130 & 130 & Other electrical equipment n.e.c. & 416,978 & 3,277 & 717,569 & 5,501 \\ 131 & 131 & Electronic valves tubes etc. & 350,806 & 14,654 & 665,949 & 20,584 \\ 132 & 132 & TV/radio transmitters; line comm. apparatus & 401,113 & 7,449 & 703,623 & 11,036 \\ 133 & 133 & TV and radio receivers and associated goods & 417,532 & 5,387 & 774,075 & 7,554 \\ 134 & 134 & Medical surgical and orthopaedic equipment & 379,228 & 3,454 & 667,257 & 6,001 \\ 135 & 135 & Measuring/testing/navigating appliances etc. & 420,499 & 4,093 & 791,761 & 7,103 \\ 136 & 136 & Optical instruments \& photographic equipment & 326,220 & 1,841 & 604,513 & 2,557 \\ 137 & 137 & Watches and clocks & 267,915 & 615 & 506,628 & 928 \\ 138 & 138 & Motor vehicles & 362,326 & 24,684 & 695,327 & 38,656 \\ 139 & 139 & Automobile bodies trailers \& semi-trailers & 248,525 & 1,244 & 471,373 & 2,494 \\ 140 & 140 & Parts/accessories for automobiles & 427,422 & 11,358 & 784,562 & 20,602 \\ 141 & 141 & Building and repairing of ships & 181,233 & 2,335 & 332,385 & 4,051 \\ 142 & 142 & Building/repairing of pleasure/sport. boats & 155,453 & 315 & 290,323 & 478 \\ 143 & 143 & Railway/tramway locomotives \& rolling stock & 128,073 & 1,000 & 234,083 & 1,818 \\ 144 & 144 & Aircraft and spacecraft & 258,794 & 5,122 & 481,752 & 9,596 \\ 145 & 145 & Motorcycles & 223,329 & 916 & 422,337 & 1,489 \\ 146 & 146 & Bicycles and invalid carriages & 245,497 & 334 & 446,207 & 536 \\ 147 & 147 & Other transport equipment n.e.c. & 168,167 & 68 & 312,501 & 202 \\ 148 & 148 & Furniture & 412,160 & 5,008 & 775,336 & 8,692 \\ 149 & 149 & Jewellery and related articles & 302,899 & 2,149 & 461,520 & 3,385 \\ 150 & 150 & Musical instruments & 227,752 & 150 & 434,369 & 250 \\ 151 & 151 & Sports goods & 306,837 & 549 & 573,449 & 944 \\ 152 & 152 & Games and toys & 317,275 & 1,143 & 602,799 & 1,683 \\ 153 & 153 & Other manufacturing n.e.c. & 427,790 & 1,739 & 795,776 & 2,812 \\ 154 & 154 & Manufacturing services on physical inputs owned by others & 11,693 & 686 & 19,446 & 992 \\ 155 & 155 & Maintenance and repair services n.i.e. & 18,995 & 451 & 29,468 & 649 \\ 156 & 156 & Transport & 64,771 & 62,460 & 84,876 & 79,101 \\ 157 & 157 & Travel & 43,927 & 34,333 & 59,182 & 43,011 \\ 158 & 158 & Construction & 41,874 & 82,076 & 52,970 & 102,884 \\ 159 & 159 & Insurance and pension services & 46,687 & 45,073 & 60,808 & 57,266 \\ 160 & 160 & Financial services & 49,593 & 30,048 & 64,170 & 38,248 \\ 161 & 161 & Charges for the use of intellectual property n.i.e. & 44,255 & 3,214 & 57,181 & 4,172 \\ 162 & 162 & Telecommunications, computer, and information services & 56,484 & 64,361 & 76,749 & 81,753 \\ 163 & 163 & Other business services & 61,736 & 105,546 & 79,548 & 134,632 \\ 164 & 164 & Heritage and recreational services & 8,636 & 17,053 & 14,468 & 19,846 \\ 165 & 165 & Health services & 24,006 & 66,806 & 34,038 & 84,091 \\ 166 & 166 & Education services & 34,327 & 42,817 & 44,452 & 53,616 \\ 167 & 167 & Government goods and services n.i.e. & 40,507 & 419 & 53,734 & 520 \\ 168 & 168 & Services not allocated & 38,824 & 14,099 & 38,259 & 13,491 \\ 169 & 169 & Trade-related services & 39,111 & 127,625 & 50,249 & 162,233 \\ 170 & 170 & Other personal services & 9,542 & 14,988 & 14,338 & 18,241 \\ \hline \hline \multicolumn{7}{l}{Note: `Value' is in billions of USD.} \\ \end{longtable} \clearpage \scriptsize\singlespacing \begin{longtable}{lrrrrrrr} \caption{Comparison of Number and Value of Trade Flows, By Exporter} \label{tab:compare_by_country}\\ \hline \hline & \multicolumn{3}{c}{ITPD-E R01} & \multicolumn{3}{c}{ITPD-E R02} \\ Country & Freq & Value & Share & Freq & Value & Share & \\ \hline \endfirsthead \hline & \multicolumn{3}{c}{ITPD-E R01} & \multicolumn{3}{c}{ITPD-E R02} \\ Country & Freq & Value & Share & Freq & Value & Share & \\ \hline \endhead \hline \multicolumn{7}{r}{{Continued on next page}}\\ \endfoot \endlastfoot Afghanistan&112296&9&0.00&229423&16&0.00& \\ Albania&134929&210&0.02&269251&265&0.02& \\ Algeria&131418&1123&0.10&259549&1647&0.10& \\ American Samoa&60231&1&0.00&80267&1&0.00& \\ Andorra&124044&3&0.00&250166&4&0.00& \\ Angola&80145&706&0.06&229153&889&0.05& \\ Anguilla&44262&0&0.00&79511&0&0.00& \\ Antarctica&13631&0&0.00&18830&0&0.00& \\ Antigua and Barbuda&107178&14&0.00&198542&15&0.00& \\ Argentina&298090&1293&0.11&579345&2627&0.16& \\ Armenia&109879&76&0.01&186398&105&0.01& \\ Aruba&67627&38&0.00&117469&39&0.00& \\ Australia&411231&7398&0.63&780770&11185&0.67& \\ Austria&402064&9450&0.80&759501&12824&0.77& \\ Azerbaijan&129709&722&0.06&228284&885&0.05& \\ Bahamas, The &112764&126&0.01&222837&167&0.01& \\ Bahrain&161213&273&0.02&324850&268&0.02& \\ Bangladesh&197858&598&0.05&383979&967&0.06& \\ Barbados&134317&12&0.00&250680&15&0.00& \\ Belarus&182347&495&0.04&339941&555&0.03& \\ Belgium&455415&14919&1.26&574725&18847&1.13& \\ Belgium-Luxembourg&&&&215601&965&0.06& \\ Belize&102160&12&0.00&210549&16&0.00& \\ Benin&84039&45&0.00&164077&63&0.00& \\ Bermuda&52032&348&0.03&108852&534&0.03& \\ Bhutan&38215&6&0.00&70369&9&0.00& \\ Bolivia&114868&130&0.01&244960&194&0.01& \\ Bonaire, Sint Eustatius and Saba&675&0&0.00&1831&0&0.00& \\ Bosnia and Herzegovina&166510&248&0.02&295169&343&0.02& \\ Botswana&103952&73&0.01&132829&98&0.01& \\ Bouvet Island&6357&1&0.00&8547&1&0.00& \\ Brazil&390469&24853&2.10&758309&33656&2.02& \\ British Indian Ocean Ter.&27357&0&0.00&48396&1&0.00& \\ British Virgin Islands&94766&14&0.00&173346&29&0.00& \\ Brunei&80447&156&0.01&186172&227&0.01& \\ Bulgaria&333410&1231&0.10&636249&1659&0.10& \\ Burkina Faso&83832&51&0.00&165404&117&0.01& \\ Burma&&&&4399&0&0.00& \\ Burundi&52196&33&0.00&105174&53&0.00& \\ Cambodia&131392&163&0.01&251186&255&0.02& \\ Cameroon&162520&153&0.01&312120&219&0.01& \\ Canada&447913&22170&1.88&837369&32384&1.94& \\ Cape Verde&66543&7&0.00&108745&9&0.00& \\ Cayman Islands&52393&15&0.00&98880&80&0.00& \\ Central African Republic&59182&6&0.00&125366&11&0.00& \\ Chad&43268&62&0.01&83957&69&0.00& \\ Chile&247812&2213&0.19&497905&3537&0.21& \\ China&484848&80839&6.84&890333&153320&9.19& \\ Christmas Island&20039&0&0.00&34913&1&0.00& \\ Cocos (Keeling) Islands&28942&0&0.00&53364&0&0.00& \\ Colombia&248553&1445&0.12&494103&5649&0.34& \\ Comoros&24837&1&0.00&52456&1&0.00& \\ Congo, Democratic Republic of the &85860&63&0.01&151370&101&0.01& \\ Congo, Republic of the &99841&158&0.01&196664&232&0.01& \\ Cook Islands&28778&1&0.00&57512&1&0.00& \\ Costa Rica&204397&767&0.06&402059&1205&0.07& \\ Cote d'Ivoire&173161&207&0.02&362197&326&0.02& \\ Croatia&251509&1089&0.09&446512&1512&0.09& \\ Cuba&116830&30&0.00&228167&47&0.00& \\ Curacao&25205&18&0.00&45925&20&0.00& \\ Cyprus&238844&596&0.05&482824&745&0.04& \\ Czech Republic&361673&5735&0.49&610129&7555&0.45& \\ Czechoslovakia&&&&18193&20&0.00& \\ Denmark&417392&7528&0.64&794665&9868&0.59& \\ Djibouti&50921&2&0.00&98025&3&0.00& \\ Dominica&96735&2&0.00&197922&3&0.00& \\ Dominican Republic&188147&347&0.03&354962&762&0.05& \\ East Timor&39710&3&0.00&51231&5&0.00& \\ Ecuador&210291&1037&0.09&416984&1509&0.09& \\ Egypt, Arab Rep.&299337&1244&0.11&578434&1727&0.10& \\ El Salvador&135014&168&0.01&266438&350&0.02& \\ Equatorial Guinea&34080&138&0.01&61728&160&0.01& \\ Eritrea&46703&10&0.00&73379&16&0.00& \\ Estonia&250130&559&0.05&438713&728&0.04& \\ Ethiopia (excludes Eritrea)&169668&167&0.01&288727&213&0.01& \\ Ethiopia (includes Eritrea)&&&&1190&1&0.00& \\ Faeroe Islands&41075&10&0.00&87466&20&0.00& \\ Falkland Islands&17524&3&0.00&34174&4&0.00& \\ Fiji&112434&26&0.00&212613&45&0.00& \\ Finland&345940&5826&0.49&663109&7787&0.47& \\ France&488779&60567&5.13&898592&80109&4.80& \\ Free Zones&&&&120252&80&0.00& \\ French Guiana&12&0&0.00&3030&0&0.00& \\ French Polynesia&63579&2&0.00&126055&6&0.00& \\ French Southern Territories&11443&0&0.00&17358&0&0.00& \\ Gabon&105156&106&0.01&202110&155&0.01& \\ Gambia, The&73257&3&0.00&146880&8&0.00& \\ Gaza Strip&&&&51936&10&0.00& \\ Georgia&190823&59&0.00&334295&184&0.01& \\ German Democratic Republic&&&&4566&7&0.00& \\ Germany&505048&82860&7.02&853468&110866&6.64& \\ Ghana&180850&215&0.02&361463&353&0.02& \\ Gibraltar&57828&6&0.00&123294&7&0.00& \\ Greece&340433&5218&0.44&676245&6369&0.38& \\ Greenland&29919&11&0.00&62588&19&0.00& \\ Grenada&58708&1&0.00&121186&3&0.00& \\ Guadeloupe&&&&6672&1&0.00& \\ Guam&36830&1&0.00&46379&1&0.00& \\ Guatemala&174822&140&0.01&355412&217&0.01& \\ Guinea&97025&60&0.01&187720&106&0.01& \\ Guinea-Bissau&18911&15&0.00&38541&18&0.00& \\ Guyana&98856&19&0.00&193572&33&0.00& \\ Haiti&66869&12&0.00&144619&19&0.00& \\ Heard Island and McDonald Islands&4358&0&0.00&5500&0&0.00& \\ Holy See&21378&0&0.00&32114&0&0.00& \\ Honduras&145168&119&0.01&296890&184&0.01& \\ Hong Kong&387871&7447&0.63&544368&9263&0.56& \\ Hungary&322083&3640&0.31&628484&4859&0.29& \\ Iceland&190033&337&0.03&379423&418&0.03& \\ India&458718&22533&1.91&854103&37656&2.26& \\ Indonesia&398769&5064&0.43&749824&6701&0.40& \\ Iran&250447&3118&0.26&484638&6887&0.41& \\ Iraq&71569&822&0.07&141061&1196&0.07& \\ Ireland&332240&7561&0.64&653724&9726&0.58& \\ Isle of Man&54&0&0.00&81&0&0.00& \\ Israel&302920&4061&0.34&572554&5699&0.34& \\ Italy&476930&51938&4.40&885861&69084&4.14& \\ Jamaica&157336&68&0.01&309421&101&0.01& \\ Japan&418911&122564&10.38&803909&150295&9.01& \\ Jordan&195097&234&0.02&390342&512&0.03& \\ Kampuchea&&&&925&0&0.00& \\ Kazakhstan&161252&1393&0.12&278004&1902&0.11& \\ Kenya&224274&465&0.04&460734&575&0.03& \\ Kiribati&22107&1&0.00&41980&1&0.00& \\ Korea, North&180083&92&0.01&363968&666&0.04& \\ Korea, South&404257&28664&2.43&769156&36961&2.22& \\ Kuwait&180226&1564&0.13&348744&2006&0.12& \\ Kyrgyzstan&104934&76&0.01&185663&114&0.01& \\ Laos&76981&66&0.01&151492&103&0.01& \\ Latvia&241274&631&0.05&429994&836&0.05& \\ Lebanon&269503&65&0.01&530272&128&0.01& \\ Lesotho&35750&14&0.00&56895&21&0.00& \\ Liberia&66270&19&0.00&136865&33&0.00& \\ Libya&73995&504&0.04&144799&659&0.04& \\ Liechtenstein&3034&11&0.00&4796&15&0.00& \\ Lithuania&268554&825&0.07&474033&1157&0.07& \\ Luxembourg&255449&2690&0.23&331272&3325&0.20& \\ Macao&107253&40&0.00&218185&60&0.00& \\ Macedonia&143330&195&0.02&259273&257&0.02& \\ Madagascar&143136&63&0.01&284340&100&0.01& \\ Malawi&110255&93&0.01&210465&136&0.01& \\ Malaysia&382376&5127&0.43&732886&7169&0.43& \\ Maldives&48908&3&0.00&94487&5&0.00& \\ Mali&121058&86&0.01&231263&133&0.01& \\ Malta&196532&359&0.03&390660&496&0.03& \\ Marshall Islands&30833&11&0.00&53172&14&0.00& \\ Martinique&&&&4335&2&0.00& \\ Mauritania&69112&33&0.00&136198&48&0.00& \\ Mauritius&178090&135&0.01&342821&142&0.01& \\ Mayotte&12459&0&0.00&12110&0&0.00& \\ Mexico&332546&20032&1.70&638936&27047&1.62& \\ Micronesia, Federated States of &16044&1&0.00&24886&2&0.00& \\ Moldova&134406&111&0.01&249497&178&0.01& \\ Monaco&4&0&0.00&3084&18&0.00& \\ Mongolia&81905&133&0.01&149529&199&0.01& \\ Montenegro&49748&34&0.00&75175&34&0.00& \\ Montserrat&33768&0&0.00&62821&0&0.00& \\ Morocco&254319&767&0.06&508276&1024&0.06& \\ Mozambique&120864&126&0.01&246005&185&0.01& \\ Myanmar&101074&247&0.02&225652&185&0.01& \\ Namibia&194306&74&0.01&264055&102&0.01& \\ Nauru&37406&1&0.00&75568&1&0.00& \\ Nepal&112751&88&0.01&221096&198&0.01& \\ Netherlands&484893&22172&1.88&893114&28554&1.71& \\ Netherlands Antilles&71673&26&0.00&141910&31&0.00& \\ Neutral Zone&&&&84&0&0.00& \\ New Caledonia&96687&24&0.00&131706&30&0.00& \\ New Zealand&326632&2747&0.23&628514&3668&0.22& \\ Nicaragua&124986&64&0.01&259239&98&0.01& \\ Niger&112934&73&0.01&224720&112&0.01& \\ Nigeria&196703&5460&0.46&387871&7316&0.44& \\ Niue&23575&0&0.00&35187&1&0.00& \\ Norfolk Island&10002&0&0.00&15341&0&0.00& \\ Northern Marianas&20697&0&0.00&31301&0&0.00& \\ Norway&324450&8938&0.76&626619&12102&0.73& \\ Oman&171143&560&0.05&349990&828&0.05& \\ Pakistan&302648&1627&0.14&576245&3110&0.19& \\ Palau&15097&0&0.00&25746&1&0.00& \\ Palestine&41745&35&0.00&57025&90&0.01& \\ Panama&204284&122&0.01&406514&242&0.01& \\ Papua New Guinea&70730&87&0.01&146826&240&0.01& \\ Paraguay&108819&124&0.01&226712&297&0.02& \\ Peru&224824&2469&0.21&444669&3647&0.22& \\ Philippines&313383&2322&0.20&600269&3270&0.20& \\ Pitcairn&18244&0&0.00&28642&0&0.00& \\ Poland&389642&10704&0.91&740321&15272&0.92& \\ Portugal&366106&5327&0.45&712245&6850&0.41& \\ Puerto Rico&25&0&0.00&3866&11&0.00& \\ Qatar&166066&1385&0.12&304684&2002&0.12& \\ Reunion&&&&6199&0&0.00& \\ Romania&308195&3740&0.32&591582&5270&0.32& \\ Russia&350310&10972&0.93&598051&19586&1.17& \\ Rwanda&71646&56&0.00&139359&74&0.00& \\ Saint Barthelemy&1151&0&0.00&4221&0&0.00& \\ Saint Helena, Ascension, and Tristan da Cunha&38225&0&0.00&66381&0&0.00& \\ Saint Kitts and Nevis&54605&2&0.00&106639&3&0.00& \\ Saint Lucia&67450&3&0.00&136241&6&0.00& \\ Saint Pierre and Miquelon&9439&0&0.00&24928&0&0.00& \\ Saint Vincent and the Grenadines&63868&4&0.00&129044&6&0.00& \\ Samoa&47287&3&0.00&70773&4&0.00& \\ San Marino&62214&3&0.00&83642&6&0.00& \\ Sao Tome and Principe&43583&0&0.00&80426&0&0.00& \\ Saudi Arabia&271794&4187&0.35&544584&7044&0.42& \\ Senegal&176385&70&0.01&335543&163&0.01& \\ Serbia&155497&725&0.06&220768&899&0.05& \\ Serbia and Montenegro&27390&78&0.01&19275&18&0.00& \\ Seychelles&86160&12&0.00&162028&15&0.00& \\ Sierra Leone&109954&29&0.00&214410&35&0.00& \\ Singapore&387573&4309&0.36&742896&6316&0.38& \\ Sint Maarten&4914&0&0.00&11207&0&0.00& \\ Slovakia&292232&2346&0.20&490703&2979&0.18& \\ Slovenia&285543&1221&0.10&499961&1566&0.09& \\ Solomon Islands&36306&2&0.00&69364&11&0.00& \\ Somalia&43068&5&0.00&91256&7&0.00& \\ South Africa&415897&2320&0.20&537940&2573&0.15& \\ South Georgia and South Sandwich Islands&4831&0&0.00&6870&0&0.00& \\ South Sudan&1431&11&0.00&4852&16&0.00& \\ Soviet Union&&&&11842&61&0.00& \\ Spain&444857&32416&2.74&836360&41005&2.46& \\ Sri Lanka&261440&484&0.04&512095&833&0.05& \\ Sudan&113170&223&0.02&224231&266&0.02& \\ Suriname&105557&32&0.00&203172&39&0.00& \\ Swaziland&147003&60&0.01&209736&78&0.00& \\ Sweden&395584&10966&0.93&750382&15233&0.91& \\ Switzerland&428383&14240&1.21&809083&19930&1.19& \\ Syria&192354&353&0.03&356368&338&0.02& \\ Taiwan&396874&8967&0.76&747876&9397&0.56& \\ Tajikistan&56713&48&0.00&108359&97&0.01& \\ Tanzania&193263&147&0.01&370769&235&0.01& \\ Thailand&425045&3738&0.32&804167&5557&0.33& \\ Togo&99571&39&0.00&203667&62&0.00& \\ Tokelau&50304&0&0.00&92329&1&0.00& \\ Tonga&28536&1&0.00&49178&1&0.00& \\ Trinidad and Tobago&161523&271&0.02&309582&325&0.02& \\ Tunisia&228179&320&0.03&456051&440&0.03& \\ Turkey&408159&6111&0.52&784803&8891&0.53& \\ Turkmenistan&53615&166&0.01&101328&198&0.01& \\ Turks and Caicos Islands&56611&1&0.00&100439&1&0.00& \\ Tuvalu&18968&1&0.00&31994&1&0.00& \\ U.S. Minor Outlying Islands&42973&0&0.00&59472&1&0.00& \\ U.S. Virgin Islands&71&0&0.00&75&0&0.00& \\ Uganda&145506&125&0.01&278071&168&0.01& \\ Ukraine&335438&3416&0.29&580951&4260&0.26& \\ United Arab Emirates&373205&2366&0.20&710981&3854&0.23& \\ United Kingdom&493871&58329&4.94&917582&75393&4.52& \\ United States&513572&298703&25.29&939248&433738&25.99& \\ Uruguay&173672&196&0.02&351309&267&0.02& \\ Uzbekistan&83616&86&0.01&164042&437&0.03& \\ Vanuatu&36771&7&0.00&65787&9&0.00& \\ Venezuela&182439&1152&0.10&367176&1390&0.08& \\ Vietnam&317891&2274&0.19&597083&2874&0.17& \\ Wallis and Futuna Islands&10395&0&0.00&18052&0&0.00& \\ West Germany&&&&62427&975&0.06& \\ Western Sahara&6386&0&0.00&10639&0&0.00& \\ Western Samoa&&&&12938&0&0.00& \\ Yemen&108046&176&0.01&190141&257&0.02& \\ Yemen, North&&&&3331&1&0.00& \\ Yemen, South&&&&28&0&0.00& \\ Yugoslavia&&&&12311&23&0.00& \\ Zaire&&&&44302&9&0.00& \\ Zambia&114920&107&0.01&226129&270&0.02& \\ Zimbabwe&136006&49&0.00&271870&99&0.01& \\ \hline \hline \multicolumn{8}{l}{Notes: `Value' is in billions of USD.} \\ \multicolumn{8}{l}{\phantom{Notes: }`Share' denotes the value share per year.} \\ \end{longtable} \normalsize\doublespacing \clearpage @Article{Borchertetal2022a, author={Borchert, Ingo and Larch, Mario and Shikher, Serge and Yotov, Yoto V.}, title={{The International Trade and Production Database for Estimation -- Release 2 (ITPD-E-R02)}}, journal={USITC Working Paper 2022--07--A}, year=2022, } @Article{Borchertetal2021, author={Borchert, Ingo and Larch, Mario and Shikher, Serge and Yotov, Yoto V.}, title={{The International Trade and Production Database for Estimation (ITPD-E)}}, journal={International Economics}, year=2021, volume={166}, pages={140-166}, } @Article{Borchertetal2022, author={Ingo Borchert and Mario Larch and Serge Shikher and Yoto V. Yotov}, title={{Disaggregated Gravity: Benchmark Estimates and Stylized Facts from a New Database}}, journal={Review of International Economics}, year=2022, volume={30}, number={1}, pages={113-136}, month={February}, } @article{USITCGravity, author={Tamara Gurevich and Peter Herman}, title={The Dynamic Gravity Dataset: 1948-2016}, year={2018}, journal={USITC Working Paper 2018-02-A}, } @TECHREPORT{Wettsteinetal2019, author = {{Steen} Wettstein and {Antonella} Liberatore and {Joscelyn} Magdeleine and {Andreas} Maurer}, title = {A Global Trade in Services Data Set by Sector and by Mode of Supply (TISMOS)}, institution = {WTO}, year = {2019}, note = {available from \href{https://www.wto.org/english/res\_e/statis\_e/trade\_datasets\_e.htm}{https://www.wto.org/english/res\_e/statis\_e/ trade\_datasets\_e.htm}}, } \end{document}