metadata: authors: 0: author: Herrera Dappe,Matias
1: author: Lebrand,Mathilde Sylvie Maria
2: author: Van Patten,Diana
count: India,Bangladesh
docna: 0: docna: Bridging Bangladesh and India : Cross-Border
            Trade and the Motor Vehicles Agreement
docty: Policy Research Working Paper
subtopic: International Trade and Trade Rules,Transport Services,Urban Housing and Land Settlements,Urban Housing,Municipal Management and Reform,Urban Governance and Management,Trade and Multilateral Issues
teratopic: Communities and Human Settlements,Public Sector Development,Urban Development,International Economics and Trade,Transport
abstracts: cdata!: This paper studies the effects of
            removing transport and trade barriers between Bangladesh and
            India on aggregate real income and the distribution of
            population and real income within both countries. The paper
            uses a spatial general equilibrium model calibrated to these
            two economies, along with road network travel time
            calculated using GPS data, to measure changes in economic
            outcomes given changes in trade costs across regions. The
            paper focuses on the Motor Vehicles Agreement between
            Bangladesh, Bhutan, India, and Nepal and full transport and
            trade integration between Bangladesh and India. The
            counterfactual exercises show that decreasing transport and
            trade barriers between Bangladesh and India can lead to up
            to a 7.6 percent increase in national real income for India
            and a 16.6 percent increase for Bangladesh.
geo_reg_key: 517198,517191,517212
repnme: repnme: Bridging Bangladesh and India :
            Cross-Border Trade and the Motor Vehicles Agreement
display_title: Bridging Bangladesh and India :
            Cross-Border Trade and the Motor Vehicles Agreement
listing_relative_url: /research/2021/03/32949151/bridging-bangladesh-india-cross-border-trade-motor-vehicles-agreement
topicv3: Intraregional Trade m1326248 1175,Transport m1326661 135,Trade m1326924 698,Transport Infrastructure m1327632 1803,Land and Housing m1327648 817
publishtoextweb_dt: 2021-03-26T00:00:00Z
dois: 10.1596/1813-9450-9592
historic_topic: Communities and Human Settlements,Public Sector Development,Urban Development,International Economics and Trade,Transport
origu: Chief Economist Infrastructure (INFCE)
no_of_pages: 35
author_keys: 0: author_key: 995603
1: author_key: 1457978
model_extractions: Policy Research Working Paper 9592 Bridging Bangladesh and India Cross-Border Trade and the Motor Vehicles Agreement _Matías Herrera Dappe Mathilde Lebrand Diana Van Patten_ Transport and Digital Development Global Practice March 2021
Policy Research Working Paper 9592

# **Abstract**

This paper studies the effects of removing transport and trade barriers between Bangladesh and India on aggregate real income and the distribution of population and real income within both countries. The paper uses a spatial general equilibrium model calibrated to these two economies, along with road network travel time calculated using GPS data, to measure changes in economic outcomes given changes in trade costs across regions. The paper focuses on the Motor Vehicles Agreement between Bangladesh, Bhutan, India, and Nepal and full transport and trade integration between Bangladesh and India. The counterfactual exercises show that decreasing transport and trade barriers between Bangladesh and India can lead to up to a 7.6 percent increase in national real income for India and a 16.6 percent increase for Bangladesh.

This paper is a product of the Transport and Digital Development Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at mdappe@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# Bridging Bangladesh and India: Cross-Border Trade and the Motor Vehicles Agreement<sup>_∗_</sup>

Mat ́ıas Herrera Dappe<sup>_†_</sup> Mathilde Lebrand<sup>_‡_</sup> Diana Van Patten<sup>_§_</sup> World Bank World Bank Princeton University March 2021 _Keywords:_ Agglomeration economies, economic integration, spatial general equilibrium, trade and geography, transport corridors.

_JEL Classification:_ F12, F15, O18, R11, R12, R13.

> _∗_ This work is a product of the staff of the World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of the World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on maps in this work do not imply any judgment on the part of the World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries.

> _†_ mdappe@worldbank.org.

> _‡_ mlebrand@worldbank.org.

> _§_ vanpatten@princeton.edu.
# **1 Introduction**

The Bangladesh-India border is the fifth-longest border in the world. It is so thick that it is more costly for Bangladesh and India to trade with each other than for either of them to trade with Germany. As a result of the thick border, bilateral trade represents only about 10 percent of Bangladesh’s trade and 1 percent of India’s trade. These figures compare poorly with East Asian and Sub-Saharan African economies, where intraregional trade accounts for 50 percent and 22 percent of total trade, respectively.

Lack of transport integration is an important contributor to the thickness of the border. Because trucks are not allowed to cross borders, cargo must be transloaded, adding to transport and trade costs. On average, crossing the border at Petrapole-Benapole, the most important border post between the two countries, takes 138 hours, including 28 hours spent transloading cargo. In contrast, the time to cross borders handling similar volumes of traffic in other regions of the world, including East Africa, is less than six hours.

Lack of transport integration between Bangladesh and India also means that Indian trucks are not allowed to transit through Bangladesh. As a result, India’s northeast states are connected with the rest of India only through the Siliguri corridor, a 27-kilometer wide tract of land commonly known as the ”chicken’s neck.” The transit restriction leads to long and costly routes between northeast India and the rest of India and the world. Goods from Agartala, for example, travel 1,600 kilometers through the Siliguri corridor to reach Kolkata Port instead of 450 kilometers through Bangladesh.

The Motor Vehicles Agreement (MVA) between Bangladesh, Bhutan, India, and Nepal (known as the BBIN countries), signed in 2015 but not yet implemented, seeks to facilitate the unrestricted cross-border movement of cargo, passenger, and personal vehicles between BBIN countries. Under the agreement, trucks carrying export-import or transit cargo can move inside the territories of other countries without transshipping to local trucks at border land ports.

This paper explores the aggregate and regional effects of changing current transport and trade barriers between Bangladesh and India on aggregate real income and on the distribution of population and real income across regions within both countries. It uses a spatial general equilibrium model calibrated to these two economies, along with road network travel time calculated using GPS data, to measure changes in economic outcomes given changes in trade costs across regions.

The paper examines three scenarios. The counterfactuals explore the potential benefits 2
for two neighboring economies of relaxing transport and trade barriers, based on policies currently being considered. The analysis focuses on the aggregate impact of increasing market access and the extent to which it affects not only border regions but locations far away from the countries’ borders.

The model developed allows for multiple regions (districts and states) that trade differentiated products while facing bilateral trade costs. As in Allen and Arkolakis (2014), the trade costs are proportional to the least-cost route connecting any pair of locations, given the countries’ road networks. Workers who consume traded and nontraded goods are imperfectly mobile across regions. Along the lines of Krugman (1991), each region features free entry of firms, each with increasing returns, and thus positive agglomeration externalities.

The quantitative exercises are based on data on economic activity (employment and wages) across districts in Bangladesh and states in India, along with GIS data on the road network of each country. The GIS data allow changes in trade costs to be estimated more precisely than they could be using standard distance-based measures, given the heterogeneous conditions of roads in these countries. Using these data, we recover trade flows across locations and calibrate the rest of the parameters to different moments. We use standard values from the literature for the elasticities in the model.

By reducing transport and trade costs, the MVA would reduce the prices of final goods and intermediate inputs. These reductions would lead to increases in national real income of up to 7.6 percent in India and 16.6 percent in Bangladesh. Increasing the competitiveness of some states and districts more than others would increase economic activity in some areas, where firms would have to pay higher wages to attract enough workers to take advantage of the improved competitiveness and access to markets. The relocation of economic activity would lead to reductions in spatial wage inequality in India and a marginal increase in Bangladesh.

This paper is related to several strands of research. It contributes to the international trade literature on economic geography, including the work of Cosar and Fajgelbaum (2016), Allen and Arkolakis (2019), Redding (2016), Fajgelbaum and Schaal (2020), Caliendo et al. (2018), Fajgelbaum and Redding (2014). Much of this literature focuses on trade liberalization and the role of internal geography. In contrast, we explore the role of transport integration as a main factor in reducing the thickness of the border.

The paper also contributes to work on transport infrastructure and the spatial distribution of economic activity. A growing body of literature (including Redding and Turner (2015), Allen and Arkolakis (2019), Donaldson and Hornbeck (2016), Donaldson (2018), and Bal3
boni (2019)) uses quantitative spatial models to evaluate the general equilibrium impacts of transport infrastructure investments. This paper highlights the role of transport integration for trade in both final and intermediate goods. Including trade in intermediate goods magnifies the gains from better integration.

The rest of the paper is structured as follows. Section 2 introduces our quantitative model, which incorporates a role for trade in both intermediate and final goods. Section 3 presents the data and the calibration. Section 4 describes the counterfactuals we assess. Section 5 presents the main results of the simulation. Section 6 shows how these results vary when assumptions about labor mobility and agglomeration externalities change. Section 7 summarizes the paper’s main conclusions.

# **2 Model**

This section presents a quantitative model that incorporates both trade in final and intermediate goods, which we apply to the economies of Bangladesh and India. The model allows for multiple regions in each country—districts in Bangladesh and states in India—that trade differentiated products while facing bilateral trade costs. Exporting regions are indexed by _i_ and importing regions by _n_ (where there are two subscripts, the first one refers to the importer). Table 2 in appendix A summarizes the notation for all the variables used in the paper.

Regions are connected by the road network, which can be used to ship goods subject to symmetric iceberg trade costs, such that _τni_ = _τin >_ 1 units must be shipped from region _i_ in order for one unit to arrive in region _n_ (or vice versa). The model follows Allen and Arkolakis (2014) in having the trade costs proportional to the least-cost route connecting any pair of locations given the road networks of both countries. Trade costs depend on distance and the quality of infrastructure linking the two locations. In particular, we assume that _τni_ is a function of distance _d_ : and calibrate _φni_ using data on speed on the road network.

Each region is endowed with an exogenous amount of effective land, _Hn_ , which is used in productive activities or for housing, and a number of workers, where each worker has one unit of labor that is supplied inelastically with zero disutility. Workers are imperfectly mobile across regions. Regions also differ by their level of amenities, _Un_ , and productivity 4
in the tradable sector. Amenities represent exogenous characteristics that are valued by individuals, such as good weather.

There are two types of agents in the economy, mobile workers and owners of immobile capital (land). Workers earn a wage _wn_ in location _n_ ; landowners in _n_ receive the total returns to land in the region where they live, _RnHn_ . The model is static; workers and capital owners therefore spend all income in the region in which they live.

# **2.1 Production**

**Final Good** Each region produces a final good that can be either consumed, used as an intermediate input by other firms, or transferred to owners of private capital used in the production of traded goods who live in other countries, in the form of net exports to the rest of the world. The quantity of the final good produced in region _n_ is:

where _Mi_ is the number of firms in region _i_ and _qni_ is the quantity that each firm located in _i_ sells to _n_ . As the good _Qn_ is priced competitively, its price is: where _pni_ is the price set in region _n_ by each firm from region _i_ .

**Tradable Goods** Firms in region _i_ produce differentiated tradable goods. To produce a variety, a firm must incur a fixed cost of _Fi_ units of an intermediate bundle _Xi_ and then produces output one-to-one from the bundle of intermediate inputs _Xi_ . The output _qi_ of each firm in region _i_ is sold in all regions _n_ subject to transport costs _τni_ , hence:

5
Assuming that firms are monopolistically competitive, they set prices equal to: where _pii_ is the domestic price equal to _pii_ = _σ−σ_ 1<sup>_p_</sup> _i_<sup>_X_with</sup><sup>_pX_</sup> _i_<sup>the cost of the bundle of factors</sup> and intermediate inputs used in production.

Constant markups and zero profits imply that all firms in _i_ have the same size ensuring zero profits.

As a result, given total production _Xi_ of the bundle of intermediate inputs used by firms, the number of firms consistent with free entry is pinned down. In particular, using the share of wages in local production from the relation (16) in appendix B, the number of firms in _i_ is:

**Intermediate Bundle** The intermediate bundle _Xi_ used by the _Mi_ monopolistic firms is produced by local perfectly competitive firms using labor _Li_ , perfectly mobile private capital _Kn_ , and tradable intermediate inputs _In_ from domestic and foreign firms through the following Cobb-Douglas production function:

The productivity shifter of each location _Ai_ may be endogenous through an agglomeration externality, where _γ_ is the aggregate total factor productivity (TFP) elasticity of the economy. The bundle of intermediate inputs is supplied under perfect competition, implying that the price of the bundle in region _i_ equals the marginal cost: where _Zi_ ( _Li_ ) takes the form 6
where _Zi_<sup>0</sup><sup>_≡_</sup> ( _Ar_<sup>_X_0</sup> _<u>i</u>_<sup>_G_</sup> )<sup>_βKX_</sup> _<u>i</u>_<sup>capturesthefundamentalcomponentofproductivity</sup><sup>_A_0</sup> _i_<sup>andthecostof</sup> private capital _r_<sup>_X_</sup> .

# **2.2 Consumer Preferences**

Workers are imperfectly mobile across locations within a country and choose the location that maximizes their utility. Their preferences are defined over consumption of final goods and residential land use. The utility of each individual worker _l_ in region _n_ is given by the product of a common component, _vn_<sup>_W_,fromlivingandworkinginlocation</sup><sup>_n_andanidiosyncratic</sup> shock, _e_<sup>_l_</sup> _n_<sup>,definingthepreferenceofindividual</sup><sup>_l_tobeinthatlocation,</sup><sup>_vn_=</sup><sup>_v_</sup> _n_<sup>_Wel_</sup> _n_<sup>.</sup> The common component depends on amenities from location _n_ , _Un_ and consumption of final goods ( _c_<sup>_W_</sup> _n_<sup>)andhousing(</sup><sup>_hW_</sup> _n_<sup>):</sup> Optimizing consumers over � _c_<sup>_W_</sup> _n_<sup>_, hW_</sup> _n_ � subject to the budget constraint, _Pnc_<sup>_W_</sup> _n_<sup>+</sup><sup>_RnhW_</sup> _n_<sup>=</sup><sup>_wn_,</sup> with _Pn_ , the aggregate price of the final good in location _n_ , _Rn_ , the land rent, and _wn_ the wage in location _n_ yields Using equilibrium prices in housing market derived in (20) yields: where _Vn_ = _Un_ � _αC_<sup>_W_</sup> � _αWC_<sup>�</sup> _αC_<sup>_KHn_</sup> �1 _−αWC_ . The random component _e_<sup>_l_</sup> _n_<sup>isassumedtofollowaFrechetdistributionandbeindependent</sup> and identically distributed, Pr � _e_<sup>_l_</sup> _n_<sup>_< x_</sup> � = _e_<sup>_−x−εW_</sup> . As a result, the fraction of workers that choose to live in region _n_ is: where _v_<sup>_W_</sup> is the workers welfare in the country, set such that the national labor-market clears.

7
## **2.3 Landowners**

Landowners have similar preferences to workers, although they may spend a different fraction of income on housing: with a budget constraint of _Pnc_<sup>_K_</sup> _n_<sup>+</sup><sup>_RnhK_</sup> _n_<sup>=</sup><sup>_Rn_.Because we assume homothetic preferences,</sup> when we aggregate the model it does not matter how many landowners there are. We therefore assume that all landowners own one unit of land. After optimization, the aggregate utility of all landowners is:

## **2.4 Equilibrium in Relative Changes**

The equilibrium is defined in changes by comparing the counterfactuals with the baseline. The counterfactuals consider shocks to trade costs _τ_ ˆ _ni_ , where _x_ ˆ denotes the value of variable _x_ in the counterfactual equilibrium relative to the initial equilibrium.<sup>1</sup> As shown in the appendix B, following standard steps as in Redding and Rossi-Hansberg (2017), the equilibˆ rium in changes is defined for employment, price indexes and wages _Ln, P_<sup>ˆ</sup> _n, w_ ˆ _n_ , and the � � welfare of workers _v_ ˆ<sup>_W_</sup> as a function of calibrated parameters and data.

Solving the system requires information on the parameters � _σ, γ, βL, βK, εW , αC_<sup>_W_</sup> � and data ˆ on import shares, export shares, and employment. Having computed _Ln, P_<sup>ˆ</sup> _n, w_ ˆ _n_ in the � � counterfactuals, we can then compute all the outcomes in each region.

# **3 Spatial Data and Calibration**

The information needed to calibrate the model comes from traditional data sources, such as surveys and geo-coded information on the transport network. It includes state- and districtlevel data on transport costs, land size, labor force, and wages.

The labor force includes the working-age population (people 15 and older). All wages are monthly and expressed in dollars. Data on labor force and wages in India come from the 2011 Periodic Labor Force Survey; data on Bangladesh come from the 2010 Labor Force Survey.

> 1 ˆ _<u>x</u>_<sup>_′_</sup> That is, _x_ = _x_<sup>,where</sup><sup>_x′_isthecounterfactualvalueand</sup><sup>_x_istheinitialvalueofvariable</sup><sup>_x_.</sup>

8
Transport costs are measured as a function of the travel time to reach other regions from the most populated district (upazila) in each Indian state (Bangladeshi district). Travel time, calculated using GIS network techniques, is the shortest time given all possible routes in the primary and secondary road network. Travel times in Bangladesh are based on actual speeds collected from more than 200 intercity road segments across the country and random speed assignment to the remaining segments based on the distribution of speeds in nearby segments. Travel times in India come from Krishna and Leemput (2018), based on GPS data from Blackbuk, an Indian logistics company that provides an online marketplace platform for freight shipments.

The elasticity of substitution between traded varieties is assumed to be _σ_ = 5, as in Head and Mayer (2014). For robustness, we also consider 4 and 6 as alternative values of this elasticity. The aggregate TFP elasticity, _γ_ , is calibrated to 0.05, following Ciccone and Hall (1996). The Cobb-Douglas share of labor, _βL_ , is set to 0.39, and the share of private capital, _βK_ , to 0.49, using data from KLEMS for India, and to 0.46 and 0.26, respectively, for Bangladesh, using to data from the World Integrated Trade Solution database (WITS). The share of housing expenditure 1 _− αC_<sup>_W_issetto0.35forBangladeshand0.44forIndia,</sup> using the share of household consumption expenditures in total expenditures from UN data. Following Fajgelbaum et al. (2015), we set the calibrated shape parameter of the random component of utility, _εW_ , at 1.5. For robustness, we considered other values for _εW_ , to study how the results vary with workers’ mobility.

# **4 Counterfactual Scenarios**

In the baseline, Indian trucks are not allowed to use Bangladeshi routes and must bypass Bangladesh through the Siliguri corridor to reach the northeast, and Bangladeshi trucks are not allowed in India. It takes an average 138 hours for cargo to cross the border between Bangladesh and India at Benapole-Petrapole, including 28 hours spent transloading cargo to and from Bangladeshi and Indian trucks.

Three scenarios were considered to assess the trade and welfare impacts of allowing Indian trucks to ply Bangladeshi roads and Bangladeshi trucks to ply Indian roads. In all of them, we assume that labor is mobile within countries and immobile across countries.

_Inefficient MVA_ . The first scenario considers the opening of new corridors through Bangladesh for Indian trucks transporting cargo to and from northeast India and Indian exports to 9
<!-- Start of picture text --> a & a<br>|<br>a<br>|<br>|<br>a<br>N<br><> c 0a30 60 120 Km —=| BorderRoad post<br>s 0 20 40 80 Miles<br><!-- End of picture text -->
efficient border crossing points outside a customs union, which tend to be up to three hours. Given the cumbersome customs clearance process currently in place, this scenario assumes that not all frictions will be removed for bilateral trade and that the border crossing time would be slightly more than three times that in the most efficient border crossing points outside a customs union.

_Full integration._ The third scenario assumes complete integration of Bangladesh and India, with no restrictions on foreign truck movements. This scenario assumes that trucks do not need to stop at the border between Bangladesh and India and that trucks can use all border posts and roads in both countries. Transport costs in this scenario are the lowest of the three scenarios.

# **5 Simulation Results**

## **5.1 Gains from the Motor Vehicles Agreement**

This subsection presents the results of the model for both MVA scenarios. It starts with the aggregate results for each country and then discusses the spatial effects. The opening of new transit routes for Indian trucks travelling to and from northeast India through Bangladesh and the removal of border frictions for bilateral trade would bring significant economic benefits to Bangladesh and India. Under the inefficient MVA scenario, income is estimated to increase by 3.4 percent in Bangladesh and 1.4 percent in India; under the efficient MVA scenario, income is estimated to increase by 11.3 percent in Bangladesh and 5.6 percent in India (Table 1). The MVA would lead to reductions in travel time and transport costs for freight, with their extent varying between the inefficient and efficient MVA scenarios, which explains the differences in income gains between the two scenarios. The reduction in transport times and costs reduces the prices of intermediate and final goods.

11
Table 1: Predicted percentage changes in income in Bangladesh and India as a result of the Motor Vehicles Agreement

|Scenarios|Bangladesh|India|
|---|---|---|
|Inefcient MVA|3.5|1.4|
|Efcient MVA|11.3|5.6|

_Notes_ : The table shows the percentage change in worker’s welfare at the country-level. We consider transit from India-Bangladesh only through the entry points outlined in the MVA.

Lower prices of final goods increase the purchasing power of consumers, and cheaper input prices make producers more competitive. The locations experiencing the largest decreases in prices become more competitive, attracting more workers and increasing their economic activity. The reductions in prices, the relocation of economic activity, and potential increases in wages lead to the increase in aggregate income in Bangladesh and India.

The effects of regional integration differ between countries because of differences in the magnitude and nature of the economic shocks on Bangladesh and India. Bangladeshi districts benefit from improved access to Indian markets. Indian states experience both an improvement in access to Bangladeshi markets and a decrease in trade costs to reach other Indian markets, with the former more important than the latter.<sup>3</sup> The gains from regional integration are much larger for Bangladesh than for India, because Bangladeshi markets are relatively small for India and Indian markets are large for Bangladesh. Small countries tend to gain more from regional integration if they remain competitive enough to export to foreign markets.

Both new transit routes and improved connectivity for bilateral trade reduce spatial inequality across states in India and increase it across districts in Bangladesh. Improvement in the connectivity of northeast Indian states with the rest of India and the increase in competitiveness of the states close to Bangladesh leads to a relocation of economic activity across the country and therefore a reduction in wage dispersion across states (Figure 2). The MVA leads to a marginal increase in wage dispersion across Bangladeshi districts, because of the significant comparative advantage of Dhaka and Chattogram districts. The rest of this section discusses the spatial effects under the efficient MVA only; the spatial patterns under the inefficient MVA are the same, with only the magnitude of the impacts changing.

> 3A scenario with no border time for transit and a 55-hour border time for bilateral freight (that is, a scenario in between the inefficient and efficient MVA scenarios) increases income in India by 1.6 percent relative to the baseline. Even if all those gains are attributed to transit, which is unlikely, improved access to Bangladeshi markets accounts for 71 percent of the income gains under the efficient MVA scenario.

12
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togram, enjoy the largest gains in real wages, where real wages increase by as much as 24 percent (see Figure 4). These districts benefit most because of their comparative advantage, which leads workers in the southwest and southeast to migrate to Dhaka, Chattogram, and other districts on the southeast-northwest axis, further concentrating employment and economic activity. Real income increases by as much as 40 percent in Dhaka and 28 percent in Chattogram, with a median increase of 8 percent (see Figure 5).

# **5.2 Gains from Full Integration**

Removing all border frictions to the movement of trucks between Bangladesh and India would reduce trade costs between Bangladesh and India further and yield greater benefits to both countries. Full transport integration between both countries would allow Indian trucks to transit through Bangladesh and to deliver exports and pick up imports anywhere in Bangladesh and Bangladeshi trucks to deliver exports and pick up imports anywhere in India using any border post. India’s national real income would increase 7.6 percent over the baseline case-43 percent more than in the efficient MVA scenario. National real income in Bangladesh would rise by 16.6 percent-47 percent higher than in the efficient MVA scenario. The additional gains would be driven by the fact that trucks transporting bilateral trade would not need to stop at the border and would be able to use any road and border post allowing them to use the lowest-cost routes.

Further reduction in transport costs under full integration intensifies the spatial patterns observed under the efficient MVA scenario, particularly in Bangladesh. In all districts in Bangladesh, the percentage gains in real income is greater under full integration than under the MVA (Figures 6 and 7). The districts along the northwest-southeast axis and those in the northeast enjoy larger gains in real incomes, because of further improvements in their competitiveness and the relocation of workers from the southwest and southeast (except Chattogram) to the rest of the country. Under both full integration and the MVA, Dhaka district enjoys the largest gains in real income, followed by Chattogram district. Under the efficient MVA, real income gains are 67 percent of the gains under full integration in Dhaka and 59 percent in Chattogram. In India, all states that enjoy gains in real income under the efficient MVA also gain under full integration, and they tend to gain more (Figures 6 and 7). For example, gains in real income in West Bengal and Meghalaya under full integration are about two-thirds larger than under the efficient MVA; in Assam, Mizoram, Nagaland, and Tripura they are 22-43 percent larger.

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that do not benefit from increase in competitiveness through better connectivity and trade opportunities.

The findings presented so far were estimated assuming low labor mobility in Bangladesh and India. Historically, the United States has been a country with high labor mobility, although it fell markedly between 1850 and 2000, from 8.5 to 4.5 (Allen and Donaldson, 2018). The migration elasticities estimated by Allen and Donaldson are much higher than the 1.5 migration elasticity we used to calibrate our model, which better represents the level of labor mobility in Bangladesh and India.

Complementary policies that increase labor mobility in Bangladesh and India would increase the aggregate gains from regional integration. The efficient MVA scenario was simulated assuming a migration elasticity of 4.5, the same as in the United States in 2000. Using this elasticity, national real income would increase 6.2 percent relative to the baseline in India (11 percent more than in the efficient MVA scenario with low labor mobility) and 14.5 percent in Bangladesh (28 percent more). Higher labor mobility also increases the spatial impacts (Figure 9). Regions that enjoy the largest gains (losses) in real income with low labor mobility enjoy even larger gains (losses) with higher labor mobility. For example, Bangladeshi districts such as Dhaka and Chattogram and Indian states such as West Bengal enjoy larger gains in real income.

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<!-- Start of picture text --> 50 -<br>= 40 .<br>oO o e a<br>]oxoO 20 . “<br>Qc e a<br>£2 3 a e Bangladesh<br>aw f on e India<br>2% 10 “es<br>c E de<br>oO<br>c of<br>£ 0 fo"<br>Oo . na<br>eoLT) ;<br>5-10 eo<br>20 =<br>-20 -10 0 10 20 30 40 50<br>Percentage change in real income under efficient MVA without agglomeration externalities<br><!-- End of picture text -->
would have to pay higher wages to attract enough workers to take advantage of their improved competitiveness and access to markets. The relocation of economic activity would lead to reductions in spatial wage inequality in India and a marginal increase in Bangladesh.

An important limitation of the analysis is that the elasticities used to calibrate the model are standard values from the empirical literature that estimates these coefficients for other countries. Some researchers (such as Baum-Snow et al. (2020)) prefer an approach based on reduced-form modeling, which first estimates a reduced-form relationship and then uses that relationship to conduct simulations. An empirical strategy would not be useful in predicting the impact of transport integration between Bangladesh and India, because no similar event has happened in the past. Once Bangladesh and India integrate and the benefits of integration are realized, an ex post empirical analysis could shed light on the mechanisms at play.

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