rafmacalaba/datause-encoder-data huggingface dataset:
<mark>WPS3564</mark>

# **Trade Costs and Location of Foreign Firms in China**<sup>**♦**</sup>

Mary Amiti<sup>*</sup> International Monetary Fund and CEPR Beata Smarzynska Javorcik<sup>#</sup> World Bank and CEPR

**Abstract:** This study examines the determinants of entry by foreign firms, using information on 515 Chinese industries at the provincial level during 1998-2001. The analysis, rooted in the new economic geography, focuses on market and supplier access within and outside the province of entry, as well as production and trade costs. The results indicate that market and supplier access are the most important factors affecting foreign entry. Access to markets and suppliers in the province of entry matters more than access to the rest of China, which is consistent with market fragmentation due to underdeveloped transport infrastructure and informal trade barriers.

## JEL Classifications: F1 F23.

Keywords: foreign direct investment, trade costs, market access, supply access.

World Bank Policy Research Working Paper 3564, April 2005 _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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> ♦ We would like to thank Caroline Freund, Mary Hallward-Driemeier, Will Martin, Stephen Redding, John Romalis, Tony Venables, Shang-Jin Wei, and participants at the Workshop on National Market Integration (World Bank and Development Research Council) in Bejing, September 2003, the Workshop on China's Economic Geography and Regional Development in Hong Kong, December 2003, and the World Bank/IMF seminars for helpful comments and suggestions. We are also grateful to the China National Bureau of Statistics (NBS) and the China Customs Office for supplying us with the data, and to Sourafel Girma for providing some additional data.

* The International Monetary Fund, 700 19th Street, Washington DC 20431. Ph (202) 623 7767. Email: mamiti@imf.org.

# The World Bank, 1818 H Street, N.W., MSN MC3-303, Washington, DC 20433. Phone: (202) 458-8485. E-mail: bjavorcik@worldbank.org.
negotiations, for example by Malaysia in financial, telecommunications and legal services; at the conclusion of the negotiations, for example by Mexico in road freight transport services; and within a certain period after the entry into force of the agreement, for example by Vietnam in telecommunications and retail services.

Second, the TPP does enhance transparency and policy certainty because parties’ services commitments cover more trading partners, more sectors and are in some cases closer to applied policies than their commitments under previous agreements. However, the TPP does not fully accomplish its goal of consolidating existing agreements between TPP countries, because the Australia, Canada, Japan, the United States are among the countries which retain the right to offer better treatment to other countries under previous agreements.

Finally, and importantly, the new rules that the TPP creates, including on state-owned enterprises, government procurement and competition policy, could enhance services market access. In particular, the TPP breaks new ground in prohibiting restrictions on international data flows, while at the same time creating unprecedented obligations on all parties to protect consumers from fraud and protect privacy. These dual obligations – on importing countries not to restrict flows and on exporting countries to protect foreign consumers – represent a model for regulatory cooperation that could elicit greater market opening if applied to other areas.

In Section II, we discuss the services-specific disciplines in the TPP. Section III describes the data sources and the measurement of services policies and commitments. Section IV provides a comparative analysis of TPP commitments. Section V describe the other rules in the agreement that matter for services trade, and Section VI concludes.

# **II. SERVICES-SPECIFIC DISCIPLINES IN THE TPP: HOW MUCH VALUE ADDED?**

In this section, we describe the key disciplines on services trade in the TPP. These disciplines are distributed across several provisions, of which the most important are: Chapter 9 on investment across all goods and services sectors; Chapter 10 on cross border trade in services; Chapter 11 on financial services; Chapter 12 on temporary entry for business persons; Chapter 13 on telecommunications services; and Chapter 14 on electronic commerce. In this section, we discuss the core Chapters 9, 10, and 12 and consider aspects of other services related chapters in the following sections. Our goal is not to provide a comprehensive discussion of all aspects of the TPP but to focus on a few areas to assess how the TPP adds value to existing agreements and applied policy in the five major services sectors for which we have applied policy information. The following sections draw on information contained in TPP members’ websites, in particular, the USTR website.<sup>6</sup>

> 6 Retrievable at:  https://ustr.gov/tpp/

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<mark>majors). Those students for which tracing is possible and show no missing values on the variables of interest, that is, those in the 63%, scored above the remaining 37% in the three subjects (on average): 0.26 standard deviations in quantitative reasoning, 0.28 standard deviations in native language, and 0.29 standard deviations in foreign language. The sample of interest is then biased towards higher performing students, but such bias is similar for both education and other majors.</mark> <mark>Table 1 shows the sample distribution of the 63% of students by the semester in which they took Saber 11, split by group: teachers (8% of the sample) and other professionals. The bulk of students in the second semester of each year is explained by the fact that most students at the national level (85%) enroll in the</mark> _<mark>A school calendar</mark>_ <mark>, which goes from February to November. Students in the</mark> _<mark>B school calendar</mark>_ <mark>(2% of the population of interest), which goes from August/September to June, take the test in the first semester of the year. The remaining 13% corresponds to</mark> _<mark>flexible calendar</mark>_ <mark>students (sabbatine, fast-tracks, etc.). From these, 77% usually take the test in the second semester of each year and the remaining 23% in the first one.</mark>

**Table 1.** Sample size

||||<br>**Teac**|<br>**hers**|<br>**Otherprof**|<br>**essionals**|
|---|---|---|---|---|---|---|
|**Test**<br>|**Year**|**Semester**|**Number of**<br>**observations**|**Percentage**<br>**(%)**|**Number of**<br>**observations**|**Percentage**<br>**(%)**|
||002|I|36|0.87|393|0.84|
|||II|300|7.22|3038|6.52|
||003|I|55|1.32|585|1.25|
|||II|485|11.67|4362|9.36|
||004|I|58|1.40|830|1.78|
|**Saber 11**<br>||II|700|16.85|6773|14.53|
||005|I|101|2.43|1310|2.81|
|||II|958|23.06|10288|22.07|
||2006|I|103|2.48|2133|4.58|
|||II|1278|30.76|14649|31.42|
||2007|I|81|1.95|2256|4.84|
|**Saber Pro **|**2011**|**II**|**4155**|**100.00**|**46617**|**100.00**|

Source: Authors’ compilations based on ICFES data.

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role of local governments in a positive light given the strong record of Chinese GDP growth. But firm-level micro-econometric studies on whether and how local governments aided economic development are rare, in part because it is difficult to identify and measure specific government interventions at the local level and to uncover firm-level information on when and how those interventions provided assistance. Ours is, therefore, the first micro-level study to our knowledge of China that attempts to link specific forms of market facilitation by local governments to firm-level efficiency.

The rest of the paper is organized as follows. Section 2 describes the data and variables, while Section 3 presents the main analysis and results. Although the associations we find are strong ones, and the patterns indicate that the firms least equipped to access formal markets benefited most from these local government interventions, the plausibility of our interpretation should not rest on regressions alone. In Section 4, therefore, we provide detailed case study descriptions of how a handful of local government initiatives – both informational and financial – functioned during this period. Section 5 concludes.

# **2. Data and Variables**

Our data come from a survey of firms for the period between 2000 and 2002, conducted in early 2003 by the World Bank on the investment climate in China. Firms were drawn from 18 cities that were selected to achieve balanced representation across five regions: Northeast (including Benxi, Changchun, Dalian, and Harbin), coastal (including Hangzhou, Jiangmen, Shenzhen, and Wenzhou), central (including Changsha, Nanchang, Wuhan, and Zhenzhou, southwest (including Chongqing, Guiyang, Kunming, and Nanning), and northwest (including Langzhou and Xi’an). The total sample is composed of 2,400 firms, 100 or 150 from each city.

The questionnaire has two parts. Part one, based on interviews with the manager of a firm, contains questions on general information about the firm and the manager, innovation, market environment, relationships with clients and suppliers, location of manufacturing plant, relations with government, and international trade. Part two is based on interviews with the firm’s accountant and personnel manager, who provided quantitative information on production, costs, employee training, schooling, and wages. While most of the qualitative questions pertained only to the year 2002, many quantitative questions also requested information for 2000 to 2002.

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Figure 10. Reasons for Not having an Account, 2011 <!-- Start of picture text --> 80 72<br>70<br>70 66<br>60 54<br>50<br>50 46<br>40 36<br>27 27 29<br>3020 14 22 21 19 21 15 14 22 23 18 13 22 15 17 17 20 17 24 16<br>10 7 4 6 9 6 5<br>0<br>Turkey BRIC Rest of Developing World Developed World Rest of ECA<br>Too Far Away Too Expensive Lack Documentation<br>Lack Trust Lack of Money Religious Reasons<br>Family Member Already Has One<br>Notes: Multiple responses allowed.<br>Sources : FINDEX 2011<br>Percent of Respondents<br><!-- End of picture text -->

# **ii. SAVINGS & SAVINGS USING A FINANCIAL INSTITUTION**

Turkey is among the countries with the lowest savings rates, both at the individual and the household level (Figure 30 and Figure 32). In the European region (which is the coverage of the LITS household level survey), Turkey has the fifth lowest savings rate among 35 countries (10 percent). In the FINDEX database, Turkey also ranks the fifth lowest in the world among 145 countries, with 9.6 percent of individuals reporting that they save.

The rate of savings at a financial institution in Turkey is low compared to the rest of the world, including only developing countries (Figure 11). In 2011, rate of savings using a bank in Turkey’s top quintile is similar to the rate of the BRICS’ lowest quintile. Turkey’s overall bank savings rate stands at 4 percent which is less than a fourth of the savings level in the BRICS countries and less than half of other ECA countries. Considering both the account usage and average income in Turkey is higher than the compared groups in 2011, Turkish individuals have a significantly lower propensity to save money. Moreover, the amount of savings differs among income groups in Turkey. Individuals in the highest income quintile are almost three times more likely to save than the members of the lowest quintile. This disparity among the bottom and top quintile groups is parallel with varying account usage levels across Turkey.

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# 5 Conclusion

Achieving universal primary education remains an elusive goal in many developing countries. While governments can choose to invest greater amounts in providing and subsidizing the costs of public schooling, the budgetary implications of such a task are daunting. Private educational provision is an increasing presence, particularly in developing countries, with shares exceeding 20 percent at the primary level in a large number of countries.

The crucial question is whether the market can oer aordable and quality education at a scale that can complement the public sector in achieving universal enrollment goals. This paper underscores that for this to happen local supply-side constraints need to be alleviated. While not surprising at the aggregate level, the result that (teacher) supply curves are not perfectly elastic at the village level can generate poverty traps in credit-constrained environments (Ljungqvist 1993 and Banerjee 2004).<sup>23</sup> Higher returns to education may perversely lead to declines in the provision of education if the returns increase as a consequence of higher wages in non-teaching professions. Moreover, locally upward-sloping supply curves have consequences for the pricing of voucher schemes. Depending on the elasticity of supply, increases in demand through vouchers may lead to simultaneous increases in prices, a decline in quality (in price-capped schemes), or both.

In contrast to calls for larger primary school investments at the expense of secondary schools, our ndings suggest that both play a role. Public investments in secondary schools increase the supply of potential teachers locally and foster the growth of private schools, potentially leading to a virtuous cycle of human capital accumulation.

The changes documented in this paper represent more than just a sectoral realignment from public to private schools. Work in Pakistan and other countries suggests that the

> 23An upward sloping supply curve at the local level reects supply constraints in the educational sector as it arises due to local labor market restrictions. There is a natural parallel with the literature on credit constraints. Evidence for such constraints is whether the cost of borrowing increases with the amount for individual rms. Again, that the cost of borrowing increases with the amount at the aggregate level is not surprising; conversely, rm-specic borrowing costs that increase with the amount borrowed lead to several important policy conclusions (see Banerjee and Duo 2004).

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foregone earnings for primary education graduates. The direct resource cost of schooling appears in Table 5. The resulting returns appear in Table 6.

**<u>Table 5: Cost per Student/Year</u>**

|Level of Education|Cost 2017 ($US)|
|---|---|
|Primary|1,582|
|Secondary|1998<sup>a</sup>|
|Higher|3736|

Source: Turkstat (2018) website a. Average of lower secondary (1,600) and upper secondary upper (2395) We remark on two noteworthy findings presented in Table 6. First, comparing with Mincerian estimates of the returns to education of the previous section, we observe that the private returns by the discount method are much higher. Second, the private returns are substantially higher than the social returns, which is to be expected since social benefits are not included. The lowest private and social returns are at the secondary education level while highest returns are attained at the higher education level.

|**Table 6: Private and Social Returns to Investment in Education by**|**Discount Method (%)**|
|---|---|
|Educational level<br>Private|Social|
|Primary<br>13.0|6.0|
|Secondary<br>11.4|5.2|
|Higher<br>15.8|10.4|

# **Education’s Contribution to Economic Growth**

The estimated social rates of return can be used to assess the contribution of education to the country’s economic growth rate. In Schultz (1961)-type accounting, human capital ( _Kh_ ) is added as an independent variable in the production function, along with physical capital ( _Kp_ ) and the number of people employed: Differentiating with respect to time, to get the growth rate of output ( _gy_ ), and making elementary substitutions, one gets the estimating expression: where s _l_ is the share of labor in national income, _gl_ the rate of growth of the labor force _, I_ is the investment in physical ( _p_ ) or human ( _h_ ) capital, and _r_ the rate of return on the respective investment. Therefore, _rp_ and _rh_ correspond to the return on physical and human capital.

The ratio last term in the above expression gives the percentage growth points contribution of education investment to the rate of growth of the economy, 10
Using these estimates for the period 1995-2008, we then predict the increases in MFN tariffs to be observed in 2009 depending on whether the country faces an economic crisis and the share of neighbors predicted to have an economic crisis. MFN tariff hikes oscillate between 1 and 10 percent, with the largest percentage increases in countries with relatively low levels of MFN tariffs in 2008.

Obviously, MFN tariffs are only one of many instruments in the protectionist toolbox. Baldwin and Evenett (2009) warned us of the increase in the use of murkier forms of protectionism like during the great depression, and a similar study on the evolution of other forms of protectionism is needed. This will help us understand why countries are not using the policy space available during economic crisis. If it is the simple recognition that protectionism may not be the right response and that it can exacerbate the problem it is trying to correct, then we shouldn’t be observing increases in murkier forms of protectionism. However, if the reason has to do with country reputation and fear of signaling beggar-thy-neighbor behavior to other countries, then increases in murkier and less transparent forms of protectionism are consistent with smallest increases in MFN tariffs. Hopefully the first explanation is the correct one. But if murkier and less transparent forms of protectionism are spreading, then an adequate response by the international community would be to bring more transparency to the system.

# **References**

Achard, J., P. Rupp and J. Romini, 2008. The cost of water in manufacturing tariffs A 30 products, 33 billion dollars cost story. Policy Brief: GEM, Science-Po, December. Bacchetta, M. and R. Piermartini, 2009. The value of bindings. Manuscript, WTO Secretariat. Baldwin, R. and S. Evenett, 2008. What world leaders should do to stop the spread of protectionism. A VoxEu.org Publication: www.voxeu.org/reports/protectionism.pdf Baldwin, R. and S. Evenett, 2009. The collapse of global trade, murky protectionism, and the crisis: recommendations for the G2. A VoxEU.org Publication, <u>http://www.voxeu.org/reports/Murky_Protectionism.pdf.</u> Bouët, A., and Laborde, D. 2008. The cost of a non-Doha. Draft IFPRI Briefing Note, November.

Eichengreen, Barry and Douglas Irwin, 2009. The protectionist temptation: lessons from the Great Depression for today, <u>http://www.voxeu.org/index.php?q=node/3280.</u> Gamberoni, E. and R. Newfarmer, 2009. Trade protection: incipient, but worrisome trends. Trade Notes: The World Bank, <u>http://siteresources.worldbank.org/NEWS/Resources/Trade_Note_37.pdf</u> Irwin, D. , 1998. The Smoot-Hawley Tariff: A quantitative assessment. Review of Economics and Statistics 80: 326-34.

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Figure 16: Gold Mining and Population & Employment Levels, Contracting Mine <!-- Start of picture text --> Population Employment<br>10km 40km 70km 100km 10km 40km 70km 100km<br>Agric. Employment Non-agro Employment<br>10km 40km 70km 100km 10km 40km 70km 100km<br>Figure plots coefficients gk- at (X-10) to X km distance from the EA.<br>5<br>200<br>0 0<br>-200 -5<br>-400 -10<br>2 5<br>1 0<br>-5<br>0<br>-10<br>-1<br><!-- End of picture text --> Figure 17: Gold Mining and Night Lights, 2000 and 2010 only <!-- Start of picture text --> Effect of Gold Mining on Nightlights, Census years<br>Repeated Cross-Section First difference<br>10km 40km 70km 100km 10km 40km 70km 100km<br>+ -<br>First difference, expansion (gk ) First difference, contraction (gk )<br>10km 40km 70km 100km 10km 40km 70km 100km<br>1 .4<br>.2<br>.5<br>0<br>0<br>-.2<br>.4 .5<br>.2<br>0<br>0<br>-.2 -.5<br><!-- End of picture text -->
<!-- Start of picture text --> 25<br>q 2000 2005<br>Qo »<br>£& La Rest of the country Rest of the country~<br>ri ee —see _ a oe”<br>© 20 4 a<br>=<br>=<br>‘5oO ——~*~__Greater Rangpur<br>fis} [ inl a<br>E =~2a a<br>7S<br>= Greater Rangpur<br>e 10<br>Y) a, + | Gane” | wal<br>1 2 Ka geal 2 3 4<br>1. Boro: Ma-May 2. Aus: Jim-Aug 3. Monga: Sep-Nov 4, Aman: Dec-Feh<br><!-- End of picture text -->
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# Measurement Issues

Benefit incidence analysts inevitably face a large number of problems in developing reliable benefit allocations. We discuss below several important measurement issues, such as the unit of evaluation, the period of analysis, the grouping of households on the basis of income and other socio-economic variables, and some limitations of incidence measures.

Unit of Evaluation: Household or Individual. Benefits to individuals are the focus of many social programs. However, the fundamental economic or income unit is the household. Individuals typically combine the resources of the household, and expenditures are made either as part of a household decision or by adults on behalf of the interests of household members. While most studies examine ben:fit incidence among households, in some applications it is important to bear in mind that government programs can have important effects on the intrafamily distribution of resources among individuals, particularly in developing countries (see section m, below).

Period of Analysis: Lifetime or Current Period. Two issues--the period used to measure income and the period over which one measures benefits from govenmment programsare inportant in this context. With respect to inccme, economists generally agree that permanent or lifedme income, rather than current income, better reflects the economic position of households.

The expenditure survey data available in most countries, including the United States, do not permit a lifetime incidence analysis.<sup>78</sup> However, DeWulf (1975) argues that a lifetime perspective on income is theoreticaUy problematic. hnperfections in the capital market that preclude borrowing against future eamnings and the shortsigltzdness of consumers make the life cycle approach to fiscal incidence not particularly relevant to individual welfare. This argument may apply with pardcular force in developing countries given their widely-recognized credit market imnperfections.

Measuring program benefits, that accrue over timne raises additional research questions. For instance, many studies allocate educational benefits to households based on the participation of students in school. This distribution of benefits is then compared to the distribution of
**A4: Descriptive statistics of the prices observed in each market**

||Number of<br>Observations|Mean|Standard<br>deviation|Min|Max|
|---|---|---|---|---|---|
|Banfora|113|83.86|19.27|49.99|151.42|
|Batié|113|102.33|23.45|54.35|197.29|
|Dédougou|113|92.29|21.75|58.74|178.68|
|Diapaga|113|87.30|25.40|35.46|178.61|
|Diébougou|113|89.99|24.13|55.02|199.76|
|Djibo|113|119.57|17.21|83.81|176.88|
|Dori|113|123.79|21.26|95.81|205.08|
|Douna|113|64.65|17.28|36.17|121.23|
|Fada|113|99.56|22.96|60.28|184.23|
|Fara|113|74.83|17.78|42.56|140.97|
|Faramana|113|68.81|19.17|37.83|142.20|
|Gaoua|113|103.55|17.39|64.66|175.84|
|Gourcy|113|109.64|16.58|85.49|166.19|
|Guelwongo|113|109.20|21.47|73.28|204.69|
|Kaya|113|107.86|18.40|81.14|174.82|
|Kongoussi|113|102.54|18.45|72.12|178.26|
|Koudougou|113|100.12|19.53|68.26|173.39|
|Léo|113|91.21|20.75|56.47|175.48|
|Manga|113|103.41|21.86|66.74|195.57|
|Ouargaye|113|81.32|17.75|47.36|145.48|
|Pouytenga|113|106.17|16.23|80.34|169.71|
|Sankaryaré|113|108.39|20.06|78.40|191.04|
|Sapouy|113|88.927|22.75|50.95|182.52|
|Solenzo|113|75.80|19.76|46.38|146.83|
|Tenkodogo|113|98.27|17.41|72.22|173.60|
|Tougan|113|108.82|20.14|74.62|190.86|
|Yako|113|106.49|17.93|80.19|172.77|
|Zabré<br>**_Source: SONA_**|113<br>**_GESS and INSD_**|99.61|19.31|60.91|169.44|

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