ESCAP Trade Analytics Portal - User Manual

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User Guide and Explanatory Note for theESCAP Trade Analytics Portal(Document version 1.0 / January 2019)INTRODUCTIONThe purpose of this explanatory note is to narrate how to use the ESCAP Trade AnalyticsPortal and corresponding datasets by researchers and practitioners. While this note mainlydiscusses the datasets, its sources of data, how to use the database properly, and how tointerpret results for policy analyses, kindly refer to Shepherd (2016), “The Gravity Model ofInternational Trade: A User Guide (An updated version)” for a detailed theoretical explanation1and other technical detail and application of the gravity model of trade.ACCESSING THE PORTALTo access the ESCAP Trade Analytics Portal, please type the following link into a modernweb browser’s (such as Firefox, Chrome or Safari) address bar:https://trade.unescap.org/analyticsOVERVIEW OF DATASETS AND THEORYScreen 1 shows five available datasets that gravity models can be applied to answer policyquestions based on policymakers’ interests. The following datasets are currently available:1. Basic Gravity Model of Trade (limited variables)2. Comprehensive Gravity Model of Trade3. Trade Cost Model4. Augmented Gravity Model of Trade with NTMs and segregated sector5. Trade Cost Model with NTMs and segregated sectorScreen 1: Selecting a preferred dataset1Online available at dated-version

Basic gravity model of trade, comprehensive gravity model oftrade, and trade cost modelBasic gravity model of trade gives an introduction what the gravity model is. In brief, gravitymodel is the application of Newton’s theory in gravitation: bilateral trade flows are determinedby the size of economic mass, measured by GDP of 2 countries; and distance between 2countries. The model is widely used to quantify impacts mainly from trade-related policies.This database introduces a limited set of independent variables (i.e., gravity-related variables)and limited number of traditional policy variables (such as tariffs and RTA).Comprehensive gravity model of trade provides an exhaustive list of independent variables,especially policy-related and behind-the-border trade facilitation variables for gravity models.Table 1 classifies types of dependent and independent variables in this dataset, while Table 2categorizes additional types of independent variables in this dataset.Table 1: dependent and independent variables in “Basic Gravity Model of Trade(limited variables)”Dependent variablesClassic gravity-related independentvariables Bilateral imports GDP of reporting countries and tradingpartners Bilateral exports Geographical distance between reporting Bilateral tradecountries and trading partners Other geographical aspects between 2countries e.g., contiguity, landlockedness Cultural distance between 2 countries e.g.,sharing common language, historicallybeing the same country in the past,sharing colonial tieClassic policy-related independentvariables Bilateral tariffs Bilateral RTATable 2: additional independent variables in “Comprehensive Gravity Model of Trade”Classic gravity-related independentOther policy-related and behind-thevariablesborder independent variables GDP of reporting countries and trading Behind-the-border trade facilitation e.g.,partners and other GDP-related indicatorsEase of doing business indicator / ease ofe.g. real GDP, GDP growth, per capitatradingacrossborder/logisticsGDP (both real and nominal figure)performance index Quality of cross-border infrastructure e.g.,Liner shipping connectivityPolicymakers may examine their research questions from another perspective: policyquestions may change from how to increase trade flows to how to reduce trade costsbetween countries and which policy factors or infrastructural-related issues significantly affect

2trade costs. Trade costs from Arvis et al. (2013) , which is derived from the gravity equation ofAnderson and van Wincoop (2004), is the measure of trade hurdles in Trade Costs Model.With a similar econometric setup, the difference between Comprehensive Gravity Model ofTrade and Trade Costs Model is a set of dependent variables. While the Gravity Model ofTrade uses trade flows (either export, import or trade) as dependent variable, the Trade CostModel uses comprehensive trade costs (either include or exclude tariff costs) as dependentvariables.SETTING YOUR PREFERENCESTo illustrate how to use these three databases, the Basic Gravity Model of Trade Databaseis used as an illustrative example on how to use the ESCAP Trade Analytics Portal. Screen 2and 3 shows the list of reporting and trading partner economies, respectively, available in thedataset. A user can manually click on the box in front of an economy’s name or click once onpre-defined groups of economies (e.g., Asia-Pacific (ESCAP)) in grey boxes to set theirpreferences. To de-select the pre-defined set of countries, click once again on grey box ofcorresponding pre-defined group. Once the user has finished choosing reporting economies,clicking “continue” will move the page from Screen 2 to Screen 3 to choose trading partners.Screen 3 offers an additional choice if users would like to apply the same set of reportingeconomies as trading partners. This facilitates the study of policy effect within a group ofeconomies a user is interested in. The database limits the selection up to 100 countries forboth reporters and partners. Asia-Pacific (ESCAP) as reporting economies as well as tradingpartners are used in this example.Screen 2: Selecting reporter economies2The measure suggests that the more the trade between two countries are, the lower the trade frictions, and as aresult, the lower the measure is. As trade cost measure are all inclusive i.e. it covers all factors that affect differencesbetween domestic and international prices such as geographical, quality of connectivity, behind-the-border tradefacilitation factors, decomposition of trade costs is needed to identify which factors affecting trade costs most.

Screen 3: Selecting partner economiesScreen 4 and 5 shows the list of dependent and independent variables as described in Table1. The ESCAP Trade Analytics Portal allows one dependent variable and up to 30independent variables for the model of interest. In this example, the gravity model is checkingon the effect of economic size, distance, common colonizer and tariff on trade with control onreporter, partner and year fixed effects.Equation 1: Basic setup of the gravity modellog 𝑥%&' 𝛽* 𝛽, log 𝐺𝐷𝑃%' 𝛽0 log 𝐺𝐷𝑃&' 𝛽1 log 𝑑𝑖𝑠𝑡%& 𝛽6 𝑐𝑜𝑚𝑐𝑜𝑙%& 𝛽 log 𝑡𝑎𝑟𝑖𝑓𝑓%&' 𝛽@ log 𝑡𝑎𝑟𝑖𝑓𝑓&%' 𝛾% 𝛾& 𝛾' 𝜀%&'Screen 5 also shows the selection of all variables in the model based on the basic setupabove. Clicking the information icon behind a variable will open a modal window explainingthe respective variable and listing its source. After clicking the “Continue” button and arrivingon the last selection page (see Screen 6), the user has the option to choose years as well asfixed effects (reporter, partner and year) in their model. In this example, all years and allcontrol on all types of fixed effects are chosen. Then the user can click the blue “Runregression” button to obtain the empirical results.Screen 4: Selecting a dependent variable

Screen 5: Selection of all variables in gravity model’s basic setupScreen 6: Selecting years and optionally fixed effectsINTERPRETING RESULTSScreen 7 shows the results based on the gravity model’s basic setup as shown in Equation 1.The number that is adjacent to each bar represents the beta coefficient of the model. At aglance, the model concludes that geographical distance and weighted average tariffs havenegative effects to exports. Looking into details, all coefficients are significant. Basicinterpretation based on coefficients in the regression parameter table is as follows:Distance:1% change in distance in km leads to 2.34% reduction in exports

Common colonizer:when two economies used to be under the same colonial power (e.g., Malaysia and Indiaunder British colonization), it leads to (𝑒 E 1) 100% (𝑒 ,.00M 1) 100% (3.33811)*100% 233.81% increase in exportsTariff(ji): Trade-weighted average tariff of country j charging to export of i1% change in tariff (ji) leads to 1.52% reduction in exportsTariff(ij): Trade-weighted average tariff of country i charging to export of j1% change in tariff (ij) leads to 0.83% reduction in exportsScreen 7: Sample empirical results

The regression statistics table, containing R-squared, number of observation as well asdegree of freedom of the model, is presented on the right side of regression parameter table.The dataset name, available reporters and trading partners that are included in the selectionin the models are also displayed below regression statistics table, along with years, fixedeffects, and missing countries (due to missing values).The ESCAP Trade Analytics Portal also offers several options to save the result of the model,including: (1) exporting the results to excel (CSV), (2) copying the results table to clipboard, (3)saving the visualization (JPEG) and, (4) printing the page or saving it as PDF. Buttons forthese options are positioned below the regression parameters table. Users can change thesetup of the model by clicking “Modify parameters” at the top right on Screen 7.TRADE POTENTIAL & TRADE SIMULATIONTwo important features of the ESCAP Trade Analytics Portal are the post-estimation optionson trade potential and trade simulation. Recall that trade potential determines how much theestimated trade is more or less than the actual one, which determines which trading partnersan economy may have room for trade improvement/growth.Equation 2: Trade potential𝑇𝑃%& OP'%QR'OS 'TRSOUVwhere TPij 1 : potential for trade expansionRW'XRY 'TRSOUVTPij 1 : exceeding trade potentialUsers can generate trade potentials based on their setup by clicking “Generate trade potential”below the regression parameters table. Screen 8 and 9 illustrate how to find trade potential ofLao PDR with all trading partners in 2015. Results in Screen 9 show that while exports of LaoPDR to Australia, China, and India have exceeded its potentials, there is lots of room forimprovement for exports to Hong Kong and Indonesia.Users can obtain trade potentials of other economies in other years by clicking the “back tothe form” or “modify conditions” buttons to go back to Screen 8 to choose the othereconomies and years of interest.Apart from trade potentials, users can also generate a trade simulation, using the sameregression result, by clicking on the “Generate trade simulation” button next to “Generatetrade potential” button, as displayed on Screen 7.Screen 10 and 11 illustrate a trade simulation or “what if” scenario to the trade model.Suppose tariff(ji), which represent tariffs of Lao PDR’s trading partners, was reduced by 5%,what would happen to exports of Lao PDR in 2015?Recall:log 𝑥0 log 𝑥, logZ[Z\ Z[Z\ 1From the example we can see that the reduction in weighted average tariff of Cambodia andChina increases Lao PDR’s exports by 0.1% and 0.2%, respectively. Again, users have threeoptions to save the results: (1) exporting the results to excel (CSV), (2) copying the resultstable to clipboard, and (3) printing page or saving the page as PDF. Users can obtainsimulation of other economies and/or in other years by clicking “back to the form” or “modifyconditions” to go back to Screen 10 to choose the other economies and years of their interest

Screen 8: Exploring trade potential of Lao PDR with trading partners in 2015Screen 9: Results of trade potential of Lao PDR and its trading partners in 2015

Screen 10: Trade simulation: what if tariff of Lao PDR’s trading partners’ tariff werereduced by 5%Screen 11: Trade Simulation results when trading partners of Lao PDR reduced tariffsby 5% in 2015

Augmented Gravity Model of Trade with NTMs and segregatedsector and Trade Cost Model with NTMs and segregated sectorThe ESCAP Trade Analytics Portal provides additional datasets with regard to NTMs:Augmented Gravity Model of Trade with NTMs and segregated sector and Trade CostModel with NTMs and segregated sector. As described in previous section, both modelsprovide the same set of independent variables; however, imports and trade costs areprovided in augmented gravity model and trade costs model, respectively. Note that data onNTMs are based on 6-digit HS2012 i.e., corresponding trade data associated with NTMs areavailable from 2012 onward. Therefore, scope of studies regarding to NTMs is currentlylimited to only 2012-2016. Table 3 shows variables available in the model with NTMs.Table 3: dependent and independent variables in models with NTMs (4) and (5)Dependent variable: imports/trade costsClassicgravity-relatedindependentNTM-related variablesvariables GDP of reporting countries and trading Average non-tariff measures imposedpartners (with lagged term) Other NTM measures such as coverage Geographical distance between reportingratio, frequency index, prevalence scorecountries and trading partnersand regulatory distance Other geographical aspects between 2 Factor endowment: land, capital, and laborcountries e.g., contiguity, landlockedness Cultural distance between 2 countriese.g.,sharingcommonlanguage,historically being the same country in thepast, sharing colonial tieClassicpolicy-relatedindependentOther policy-related and behind-thevariablesborder independent variables Bilateral tariffs (with lagged term) Behind-the-border trade facilitation e.g.,Ease of doing business indicator / ease of Bilateral RTA (with lagged term)tradingacrossborder/logisticsperformance index Quality of cross-border infrastructure e.g.,Liner shipping connectivityTo choose the dataset, again, go back to the homepage of the ESCAP Trade Analytics Portaland on the homepage select either database (4) for augmented gravity model or database (5)for trade costs model with NTMs. Follow Screen 2 to 3 to select reporting countries, andpartner countries of interests. Screen 12 shows the list of dependent and independentvariables, including NTMs.

Screen 12: List of independent variables in models with NTMsThe additional feature in the model with NTMs is the ‘sector’ option, enabling sectoralspecification in the model. However, only one sector can be chosen at a time (i.e., overallgoods, agriculture or manufacturing). Once the user has chosen their variables for their modelspecification, clicking the blue “Continue” button at the bottom will lead to the step where year,sector and fixed effects can be set, as displayed in Screen 13. Finally, clicking the “Runregression” button will calculate results. The instructions in Screen 7 to 11 for resultinterpretation, post-estimation on trade potentials and trade simulation are then applicable.Screen 13: Selecting years, sector and fixed effects in models with NTMs

APPENDIX 1: VARIABLES AND METADATAThe following contains data available in the respective datasets, along with their descriptionand data sources. Please note that all variables with tag “ln ” have taken natural logfunction on their original values.Dataset 1 - 3Variable nameDescriptionln export ijNet exports of i to jln import ijNet imports of i to jln trade ijNet export and import (X M) of i to jln export iNet exports of i to worldln import iNet imports of i to worldln trade iNet export and import (X M) of i to worldln export jNet exports of j to worldln import jNet imports of j to worldln trade jNet export and import (X M) of j to worldln ctcijBi-directional trade costs of i and j (ad-valorem equivalent:%)ln ntcijln tariffrateij saln tariffrateij waln tariff ij saln tariff ij waln tariffrateji saln tariffrateji waln tariff ji saln tariff ji waBi-directional trade costs of i and j, excl tariff (ad-valoremequivalent:%)Simple average tariff in % of i charging jWeighted average tariff in % of i charging jSimple average tariff (1 (%/100)) of i charging partner jWeighted average tariff (1 (%/100)) of i charging partner jSimple average tariff in % of j charging iWeighted average tariff in % of j charging iSimple average tariff (1 (%/100)) of j charging partner iWeighted average tariff (1 (%/100)) of j charging partner iln ga tariff ijji saGeometric average of tariff ij sa and tariff ji saln ga tariff ijji waln distcontigcomlang offcomlang ethnocolonycomcolcurcolcol45smctrylandlocked ilandlocked jGeometric average of tariff ij wa and tariff ji wasimple distance (most populated cities, km)1 for contiguity1 for common official of primary language1 if a language is spoken by at least 9% of the population inboth countries1 for pairs ever in colonial relationship1 for common colonizer post 19451 for pairs currently in colonial relationship1 for pairs in colonial relationship post 19451 if countries were or are the same country1 if i is landlocked1 if j is landlockedlandlocked ijrtaln gdp i1 if i or j is landlocked1 if regional trade agreement in forceGDP (current USD) of TS:COMTRADEWITS:COMTRADEESCAP-WBTrade CostsDatasetESCAP-WBTrade CostsDatasetWITS: TRAINSWITS: TRAINSWITS: TRAINSWITS: TRAINSWITS: TRAINSWITS: TRAINSWITS: TRAINSWITS: TRAINSAuthor'scalculation basedon WITS: TRAINSAuthor'scalculation basedon WITS: ICEPIICEPIIAuthor'scalculation basedon CEPIIDe Sousa (2012)WB: Time invariant variableTime invariant variableTime invariant variableTime invariant variableTime invariant variableTime invariant variableTime invariant variableTime invariant variableTime invariant variableTime invariant variableTime invariant variableTime invariant variable1995-20151995-2016

ln gdpgrowth iln gdppc iln gdppcgrowth iln rgdp iln rgdppc iln gdp jln gdpgrowth jln gdppc jln gdppcgrowth jln rgdp jln rgdppc jln tab jln startbiz jln credit jln invest jln tax jln contract jln lsci iln lsci jGDP growth (annual %: 1 (percent/100)) of iGDP per capita (current USD) of iGDP per capita growth (annual %: 1 (percent/100)) of iGDP (constant 2010 USD) of iGDP per capita (constant 2010 USD) of iGDP (current USD) of jGDP growth (annual %: 1 (percent/100)) of jGDP per capita (current USD) of jGDP per capita growth (annual %: 1 (percent/100)) of jGDP (constant 2010 USD) of jGDP per capita (constant 2010 USD) of jOverall ease of doing business score (0-100: 0 worst, 100 best) of iTrading across border score (0-100: 0 worst, 100 best)of iStarting business score (0-100: 0 worst, 100 best) of iGetting credit score (0-100: 0 worst, 100 best) of iProtecting investors score (0-100: 0 worst, 100 best) of iPaying tax score (0-100: 0 worst, 100 best) of iEnforcing contract score (0-100: 0 worst, 100 best) of iOverall ease of doing business score (0-100: 0 worst, 100 best) of jTrading across border score (0-100: 0 worst, 100 best)of jStarting business score (0-100: 0 worst, 100 best) of jGetting credit score (0-100: 0 worst, 100 best) of jProtecting investors score (0-100: 0 worst, 100 best) of jPaying tax score (0-100: 0 worst, 100 best) of jEnforcing contract score (0-100: 0 worst, 100 best) of jLiner shipping connectivity index of iLiner shipping connectivity index of jln lpi iLogistics performance index of iWorld Bankln lpi jLogistics performance index of jWorld Bankln dtf iln tab iln startbiz iln credit iln invest iln tax iln contract iln dtf jWB: WDIWB: WDIWB: WDIWB: WDIWB: WDIWB: WDIWB: WDIWB: WDIWB: WDIWB: WDIWB: 16Doing Business2004-2016Doing BusinessDoing BusinessDoing BusinessDoing BusinessDoing BusinessDoing 0162004-2016Doing Business2004-2016Doing BusinessDoing BusinessDoing BusinessDoing BusinessDoing BusinessDoing 4-20162004-20162004-20162004-20162004-20162010, 2012, 2014,20162010, 2012, 2014,2016Dataset 4 - 5Variable nameln import ijln import iln import jDescriptionNet imports of i to jNet imports of i to worldNet imports of j to worldSourceWITS: COMTRADEWITS: COMTRADEWITS: COMTRADEESCAP-WB TradeCosts DatasetESCAP-WB TradeCosts DatasetWITS: TRAINSWITS: TRAINSWITS: TRAINSWITS: TRAINSWITS: TRAINSWITS: TRAINSWITS: TRAINSWITS: TRAINSAuthor's calculationbased on WITS:TRAINSAuthor's calculationbased on WITS:TRAINSln ctcijTrade costs: Ad-valorem equivalent (%)ln ntcijln tariffrateij saln tariffrateij waln tariff ij saln tariff ij waln tariffrateji saln tariffrateji waln tariff ji saln tariff ji waTrade costs, excluding tariff: Ad-valorem equivalent (%)Simple average tariff in % of i charging jWeighted average tariff in % of i charging jSimple average tariff (1 (%/100))of i charging partner jWeighted average tariff (1 (%/100))of i charging partner jSimple average tariff in % of j charging iWeighted average tariff in % of j charging iSimple average tariff (1 (%/100))of j charging partner iWeighted average tariff (1 (%/100))of j charging partner iln ga tariff ijji saGeometric average of tariff ij sa and tariff ji saln ga tariff ijji waGeometric average of tariff ij wa and tariff ji waln distsimple distance (most populated cities, km)CEPIIcontig1 for 012-2016Time invariantvariableTime invariantvariable

comlang offCEPIIcomlang ethno1 for common official of primary language1 if a language is spoken by at least 9% of the populationin both countriescolony1 for pairs ever in colonial relationshipCEPIIcomcol1 for common colonizer post 1945CEPIIcurcol1 for pairs currently in colonial relationshipCEPIIcol451 for pairs in colonial relationship post 1945CEPIIsmctry1 if countries were or are the same countryCEPIIlandlocked i1 if i is landlockedCEPIIlandlocked j1 if j is landlockedlandlocked ijrta1 if i or j is landlocked1 if regional trade agreement in forcecr ij modifCoverage ratio of importer i from partner jsecdum ij modif6-digit sector count of importer i and partner jfi ij modifFrequency index of importer i from partner jps ij modifPrevalence score of importer i from partner jrd A ijRegulatory distance of i and j, measured by NTM type Ard B ijRegulatory distance of i and j, measured by NTM type Brd C ijRegulatory distance of i and j, measured by NTM type Crd D ijRegulatory distance of i and j, measured by NTM type Drd E ijRegulatory distance of i and j, measured by NTM type Erd F ijRegulatory distance of i and j, measured by NTM type Frd G ijRegulatory distance of i and j, measured by NTM type Grd H ijRegulatory distance of i and j, measured by NTM type Hrd I ijRegulatory distance of i and j, measured by NTM type Ird J ijRegulatory distance of i and j, measured by NTM type Jrd L ijRegulatory distance of i and j, measured by NTM type LCEPIIAuthor's calculationbased on CEPIIDe Sousa (2012)Author's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:CEPIITime invariantvariableTime invariantvariableTime invariantvariableTime invariantvariableTime invariantvariableTime invariantvariableTime invariantvariableTime invariantvariableTime invariantvariableTime 162012-2016

rd M ijRegulatory distance of i and j, measured by NTM type Mrd O ijRegulatory distance of i and j, measured by NTM type Ord P ijRegulatory distance of i and j, measured by NTM type Prd Tech ijRegulatory distance of i and j, measured by NTM typeTechrd NTech ijRegulatory distance of i and j, measured by NTM typeNTechrd Export ijRegulatory distance of i and j, measured by NTM typeExportrd total ijRegulatory distance of i and j, measured by NTM type totalln sa ntm tech ijSimple average technical NTMs measures of importer iimposing to partner j (full set)ln sa ntm ntech ijSimple average non-technical NTMs measures of importeri imposing to partner j (full set)ln sa ntm export ijSimple average NTMs measures of importer i imposing topartner j (full set)ln sa ntm ijSimple average NTMs measures of importer i imposing topartner j (full set)ln sa ntm tech ij modifSimple average technical NTMs measures of importer iimposing to partner j (avg if there is trade data)ln sa ntm ntech ij modifSimple average non-technical NTMs measures of importeri imposing to partner j (avg if there is trade data)ln sa ntm export ij modifSimple average NTMs measures of importer i imposing topartner j (avg if there is trade data)ln sa ntm ij modifSimple average NTMs measures of importer i imposing topartner j (avg if there is trade data)ln wa ntm tech ij modifWeighted average technical NTMs measures of importer iimposing to partner j (avg if there is trade data)ln wa ntm ntech ij modifWeighted average NTMs measures of importer i imposingto partner j (avg if there is trade data)ln wa ntm export ij modifWeighted average NTMs measures of importer i imposingto partner j (avg if there is trade data)ln wa ntm ij modifln gdp iln gdppc iln agriland iln capital iln labor iln gdp jln gdppc jWeighted average NTMs measures of importer i imposingto partner j (avg if there is trade data)GDP (current US ) of iGDP per capita (current US ) of iAgricultural land of i in sq.km.Gross capital formation of i in current USDLabor force of iGDP (current US ) of jGDP per capita (current US ) of jTRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSAuthor's calculationbased on I-TIP:TRAINSWB: WDIWB: WDIWB: WDIWB: WDIWB: WDIWB: WDIWB: 62012-20162012-20162012-20162012-2016

ln agriland jln capital jln labor jln lsci iln lsci jln invest jln tax jln contract jAgricultural land of j in sq.km.Gross capital formation of j in current USDLabor force of jLiner shipping connectivity index of iLiner shipping connectivity index of jOverall ease of doing business score (0-100: 0 worst,100 best) of iTrading across border score (0-100: 0 worst, 100 best)of iStarting business score (0-100: 0 worst, 100 best) of iGetting credit score (0-100: 0 worst, 100 best) of iProtecting investors score (0-100: 0 worst, 100 best) ofiPaying tax score (0-100: 0 worst, 100 best) of iEnforcing contract score (0-100: 0 worst, 100 best) of iOverall ease of doing business score (0-100: 0 worst,100 best) of jTrading across border score (0-100: 0 worst, 100 best)of jStarting business score (0-100: 0 worst, 100 best) of jGetting credit score (0-100: 0 worst, 100 best) of jProtecting investors score (0-100: 0 worst, 100 best) ofjPaying tax score (0-100: 0 worst, 100 best) of jEnforcing contract score (0-100: 0 worst, 100 best) of jln lpi iLogistics performance index of iWorld Bankln lpi jLogistics performance index of jWorld Bankln dtf iln tab iln startbiz iln credit iln invest iln tax iln contract iln dtf jln tab jln startbiz jln credit jWB: WDIWB: WDIWB: 62012-2016Doing Business2012-2016Doing BusinessDoing BusinessDoing Business2012-20162012-20162012-2016Doing BusinessDoing BusinessDoing Business2012-20162012-20162012-2016Doing Business2012-2016Doing BusinessDoing BusinessDoing Business2012-20162012-20162012-2016Doing BusinessDoing BusinessDoing Business2012-20162012-20162012-20162010, 2012, 2014,20162010, 2012, 2014,2016Notes:1)2)3)All data from Doing Business is available from 2004 onward (DB2005). Nature of the data is 1-year lag i.e.data is mostly collected in the previous year.LSCI data is available from 2004 onward. Original data of LSCI is available for non-landlocked countriesonly. To take landlocked countries into account, average of non-landlocked countries that are adjacent tothose landlocked countries are used as proxy of quality of port connectivity.See country coverage of the dataset in Appendix.Sources:oooooooooWITS: COMTRADE: COMTRADE data through WITS. Online available at https://wits.worldbank.orgWITS: TRAINS: TRAINS data through WITS. Online available at https://wits.worldbank.orgCEPII: Online available at http://cepii.fr/CEPII/en/welcome.aspDe Sou

trade costs. Trade costs from Arvis et al. (2013)2, which is derived from the gravity equation of Anderson and van Wincoop (2004), is the measure of trade hurdles in Trade Costs Model. With a similar econometric setup, the difference between Comprehensive Gravity Model of Trade and Trade Costs Model is a set of dependent variables.While the Gravity Model of

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