rafmacalaba/datause-encoder-data huggingface dataset:
Cadot, Dutoit and Olarreaga (2010) argue that there are barriers to exit from subsistence agriculture, but the issue highlights explanations of why supply responses to market signals might be sluggish. There are two major barriers. One is risk: cash crops are riskier than food crops so that part of the difference in return is actually a risk premium (Fafchamps, 1992; Rosenzweig and Binswanger, 1993). The other barrier is related to missing markets: the differential rate of return is due in part to the shadow price of a good with missing markets such as for labor or food crops (de Janvry, Fafchamps, and Sadoulet, 1991). Notice that missing markets can arise due to variable transaction and transportation costs, fixed transaction costs (searching for partners, enforcing contracts with distant buyers, establishing quality), or sunk costs of transacting. One example is Key, de Janvry and Sadoulet (2000), who illustrate how supply responses are affected by transaction costs. Another interesting example is Cadot, Dutoit and Olarreaga (2006), who show that sunk costs can be particularly large, ranging from 124 to 153 percent of the market value of the average annual farm output in Madagascar.

We end this section with a caveat. Positive and large supply responses to price changes are always an indication that economic incentives work. However, in the context of our analytical framework of section 3, these supply responses comprise second order effects. In consequence, they are likely to generate only small welfare impacts because of the opportunity cost of the resources used in the production of different goods. While this argument does not invalidate the search for supply responses in the data, it strongly argues for a careful interpretation of the findings.

# **5 Quantifying The Mechanisms: The Case of Mexico**

In this section, we use data from Mexico to quantify the different channels uncovered by our review of the literature. The main objective is to illustrate how the mechanisms work. Our results are reported in Table 6.

We begin with the net consumer-net producer proposition. In the first panel of Table 6, we compute the first order welfare impacts of a (hypothetical) increase of 20 percent in 23
collateral will reduce the expected profit of these projects by more than that of less risky ones. Bester (1985) argued that lenders could design attractive contracts adapted to the various characteristics of borrowers, leading to perfect sorting. In this setting, the poor, who have no formal collateral, would find it difficult to come up with the needed collateral to signal themselves as low-risk endeavors and reap the benefits of a larger financial sector. The rich would thus benefit from a deeper financial sector if reforms to deal with information problems are not carried out at the same time (Banerjee and Newman, 1993; Galor and Zeira, 1993; Piketty, 1997).

In this regard, the importance of legal institutions (especially those protecting private property rights) has been stressed by the law and finance literature in explaining international differences in financial development. Where legal systems enforce private property rights, support private contracts, and protect the legal rights of investors, lenders tend to be more willing to finance firms: in other words, stronger creditor rights tend to promote financial development (see Cottarelli et al., 2003; Acemoglu and Johnson, 2005; Dehesa et al., 2007; McDonald and Schumacher, 2007; Tressel and Detragiache, 2008; and Singh et al., 2010).

But how would clearer property rights help the poor? De Soto (2003) argues that the developing world has accumulated a great deal of wealth. Much of it is “dead capital”, however, that cannot be sold or collateralized to back loans without legal institutions that establish and defend ownership and property rights. The lack of such institutions makes it particularly difficult for the poor to leverage their informal ownership into capital.

# **III.   EMPIRICAL ANALYSIS**

# **A.   Data**

Poverty is usually defined as having insufficient resources or income. In its extreme form, it is a lack of basic human needs, such as adequate food, clothing, housing, clean water, or health services. Poverty is also a lack of education or opportunity, and may be associated with insecurity and fears for the future, lack of representation and freedom. Poverty is therefore a complex reality and may have many faces, often changing from place to place and across time.

Consistent with the existing literature, the paper focuses on the economic aspect of poverty, mainly captured through three indicators of poverty: the headcount index, the poverty gap, and the income of the poorest quintile. The econometric analysis uses panel data for 37 SSA countries averaged over five-year periods from 1992 through 2006.<sup>4</sup>

> 4 The choice of period (1992-2006) is dictated by the availability of data on the institutional and poverty variables.

6
# **The Growth of Transport Sector CO2 Emissions and Underlying Factors in**

**Latin America and the Caribbean**<sup>**†**</sup>

Govinda R. Timilsina<sup>*</sup> and Ashish Shrestha Development Research Group, The World Bank, 1818 H Street, NW, Washington, DC 20433, USA

**Key Words** : Transport sector CO2 emissions, Decomposition analysis, Latin American and Caribbean countries

> † We sincerely thank Ram M Shrestha, Soma Bhattacharya, John Nash, Laura Tlaiye, Gershon Feder, Walter Vergara and LAC Transport Cluster for their valuable comments and suggestions. The views expressed in this paper are those of the authors only, and do not necessarily represent the World Bank and its affiliated organizations.

> *Fax: 1 202 522 1151; e-mail: <u>gtimilsina@worldbank.org</u>
# **_III.3. Testing the caste culture hypothesis_**

The _caste culture_ hypothesis predicts a lower level of punishment in the treatments in which the third party is a low caste member relative to the treatments in which he is a high caste member. Figure 4 provides preliminary support for this hypothesis. From the previous section, we know already that the distribution of punishments in HHH is very similar to that in HLH. Likewise, we know that punishment behaviors in LLL and LHL are similar to each other. Therefore it makes sense to pool HHH and HLH, on the one hand, and LLL and LHL, on the other hand, to examine whether punishment by high caste members is generally higher.

We find that mean _relative_ punishment imposed by high caste individuals is roughly 90 percent higher than mean relative punishment by low caste individuals (4.40 compared to 2.33). A similar picture emerges for mean _absolute_ punishment: Members of high castes punish 32 percent more than low caste members (7.63 compared to 5.76). These differences in punishment across castes are significant according to Mann-Whitney tests at _P_  0.01.

To what extent is this systematic difference in the willingness to punish a norm violation a result of differences in wealth and education across high and low castes? We collected information in post-play questions on land ownership, housing wealth, and education, which are all known to be important predictors of per capita consumption.<sup>19</sup> In this context it is important to know that although people belonging to high castes are on average wealthier, there is a substantial overlap across castes: many people who belong to a high caste are nevertheless very poor. Likewise, a significant number of low caste people have managed to acquire more wealth than poor high caste people. Therefore, we are in a position to examine the differences in punishment across castes while holding wealth constant. This shows up clearly in our sample of subjects. If we examine the distribution of castes across house quality, we find that among the 81 subjects who live in a mud house, 42% belong to a high caste and 58% belong to a low caste. If we look at those 124 subjects who live in a brick house or a mixed mud and brick house, we

> 19We show this in Table A1 in the appendix, where we use data from the 1997-98 Survey of Living Conditions in Uttar Pradesh. The table indicates that land ownership, housing wealth, and education have a large and significant impact on adult per capita consumption. Together, they explain between 30 and 40 percent of the variation in consumption for both high and low caste individuals.

19
access. They note first that data on family planning accessibility is often collected in surveys only for certain political or administrative boundaries, such as whether there is a facility in the village. However, facilities in neighboring administrative units may be closer. Using georeferenced data allows more flexible specification of boundaries, which are not constrained by administrative definitions. Secondly, they note that reported travel times to health facilities in their survey are often heaped in terms of 30 minute multiples, whereas using GIS gives no clumping, allowing better specification of functional form.

Gibson et al. (2006) examine the use of different financial channels for receiving remittances in Tonga. Transactions costs on money transfers are much higher using Western Union than when the recipient withdraws funds from an Automatic Teller Machine (ATM). There are eight ATMs on the main island of Tongatapu compared to five Western Union branches, so a branches per capita measure of access would suggest that ATMs are more accessible. However, they collect GPS coordinates of the ATMs and Western Union branches, and combine this with village-level population information from the Census and a digitalized road network to measure the share of the population within different travel distances of the two competing financial channels. Figure 1 shows their results. Although Western Union has less branches, they are more dispersed, and cover 97 percent of the population within a 10km travel distance, compared to only 77 percent of the population covered by ATMs within this distance. Figure 1 also illustrates how effective the combination of GPS data collection and mapping software can be at illustrating access in a form accessible for policymakers.

More recent health applications combine distance with measures of infrastructure quality. Hong, Montana and Mishra (2006) use the 2003 DHS in Egypt to look at the relationship between IUD contraceptive use and the quality of family planning services available. They link each household to the nearest family planning clinic within 10km, and then use detailed DHS survey data to measure the quality of the facility. Rosero-Bixby (2004) uses GPS data on census tracts and locations of health facilities in Costa Rica to assess the extent to which health reforms led to improvements in access, measuring access with a combination of distance and services provided by the facility. He notes that households may not necessarily use the nearest facility, particularly if it is low quality, and by using GIS one can calculate measures such as the density of services that meet a standard quality within a specified radius.

- 10 -
Pradhan, M, “Welfare Analysis with a Proxy Consumption Measure: Evidence from a Repeated Experiment in Indonesia,” _Fiscal Studies_ 30, 391–417, 2009. doi: 10.1111/j.1475- <u>5890.2009.00101.x.</u>

- Ravallion, M., “Measuring Aggregate Welfare in Developing Countries: How Well Do National Accounts and Surveys Agree?” _The Review of Economics and Statistics_ , 85, 645–652, 2003. doi: 10.1162/003465303322369786

- Rothbaum, J., “Comparing Income Aggregates: How do the CPS and ACS Match the National Income and Product Accounts, 2007-2012,” U.S. Census Bureau SEHSD Working Paper, -

- No. 2015-01, 2015. https://www.census.gov/content/dam/Census/library/working <u>papers/2015/demo/SEHSD-WP2015-01.pdf?cssp=SERP</u>

- Sala-i-Martin, X., “The World Distribution of Income: Falling Poverty and... Convergence, Period,” _The Quarterly Journal of Economics_ , 121, 351–397, 2006. doi: <u>10.1162/qjec.2006.121.2.351</u>

- Schündeln, M., “Multiple Visits and Data Quality in Household Surveys,” _Oxford Bulletin of Economics and Statistics_ 80, 380–405, 2018. doi: <u>10.1111/obes.12196</u>

- Serajuddin, U., H. Uematsu, H., C. Wieser, N. Yoshida, and A. Dabalen, A., “Data Deprivation: Another Deprivation to End,” _Policy Research Working Paper_ No. 7252, World Bank, Washington, DC, 2015. https://openknowledge.worldbank.org/handle/10986/21867

- Stiglitz, J., A. Sen and J. Fitoussi, “Report of the Commission on the Measurement of Economic Performance and Social Progress (CMEPSP),” 2009. <u>https://ec.europa.eu/eurostat/documents /8131721/8131772/Stiglitz-Sen-FitoussiCommission-report.pdf</u>

- Stone, R., D.G. Champernowne and J.E. Meade, “The Precision of National Income Estimates,” _Review of Economic Studies_ 9, 111–25, 1942. doi: <u>10.2307/2967664.</u>

- Subramanian, S. and D. Jayaraj. “Growth and Inequality in the Distribution of India’s Consumption Expenditure: 1983 to 2009-10,” _Economic and Political Weekly_ , 50, 7–8, 2015.

- Sundaram, K. and S.D. Tendulkar, “Poverty Has Declined in the 1990s: A Resolution of Comparability Problems in NSS Consumer Expenditure Data,” _Economic and Political Weekly_ , 38, 327–337, 2003.

- Winter, J. “Response Bias in Survey−Based Measures of Household Consumption,” _Economics Bulletin_ , 3, 1–12, 2003.

- World Bank, _Poverty and Shared Prosperity 2016: Taking on Inequality_ , World Bank, Washington, DC, 2016. <u>https://openknowledge.worldbank.org/handle/10986/25078</u>

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# **References:**

Andres, L., Vivien Foster, and J. L. Guasch (2006), <u>The impact of Privatization on Firms in the Infrastructure Sector in Latin America Countries.</u> The World Bank.

Bacon, R. W., and J. E. Besant-Jones (2001), "Global Electric Power Reform, Privatization and Liberalization of the Electric Power Industry in Developing Countries." Annual Review of Energy and the Environment 26, 331-59.

Boardman, Anthony and Aidan R. Vining (1989), “Ownership and Performance in Competitive Environments: A Comparison of the Performance of Private, Mixed, and State-Owned Enterprises,” Journal of Law and Economics, 32, pp. 1-33.

Chisari, O., A. Estache, and C. Romero (1997), "Winners and Losers from Utility Privatization in Argentina: Lessons from a General Equilibrium Model." Policy Research Working Paper 1824, World Bank, Washington, D.C.

Chong, Alberto and Florencio López-de-Silanes (2003a), “Privatization and Labor Restructuring around the World.” Manuscript. Yale University, New Haven, United States.

Chong, Alberto and Florencio López-de-Silanes (2003b), “The Truth about Privatization in Latin America”, Inter-American Development Bank, Latin American Research Network, Research Network Working Paper #R-486, October.

D’Souza, Juliet and William L. Megginson (1999). “The Financial and Operating Performance of Newly Privatized Firms in the 1990s,” J. of Finance., 54, 1397-1438.

Dussan, M. (1996). “Electric Power Sector Reform in Latin America and the Caribbean.” Working Papers Series IFM-104.

Ehrlich, Isaac, Georges Gallais-Hamonno, Zhiqiang Liu, and Randall Lutter (1994), “Productivity Growth and Firm Ownership: An Empirical Investigation,” Journal of Political Economy, 102, pp. 1006-1038.

Estache, Antonio, Marco Manacorda and Tommaso M. Valletti (2002). "Telecommunication Reforms, Access Regulation, and Internet Adoption in Latin America”. Policy Research Working Paper 2802, March .

Estache, Antonio and Martin Rodriguez-Pardina (1998), "Light and Lightening at the End of the Public Tunnel: The Reform of the Electricity Sector in the Southern Cone," World Bank Working Paper, May.

Estache, Antonio and Martin Rossi (2004) “Have Consumers Benefited from the reforms in the Electricity Distribution Sector in Latin America?” Unpublished manuscript, The World Bank.

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(Porter externalities).

Most of the empirical literature that tried to assess which type of externalities would be more favorable to local productivity growth has used employment growth to proxy for productivity growth based on the assumption that in the long-run, more productive regions would attract more workers. In general, evidence for the U.S. and Europe using employment growth as a measure of productivity growth is mixed with respect to the effect of sector concentration and diversity on regional productivity growth in manufacturing. Glaeser et al. (1992) and Peri (1992) find that local competition and urban diversity, but not regional concentration, foster employment growth in the U.S. and Italy, respectively. Combes (2000), finds evidence for France that concentration and diversity negatively affect employment growth in several sectors<sup>1</sup> . Henderson et al. (1995) find evidence of MAR externalities for the traditional capital goods industries, and of Jacobs and MAR externalities for “new” high-tech industries using data for the U.S.<sup>2</sup> .

However, using employment growth to proxy for productivity growth requires strong assumptions since employment and productivity growth need to covary positively across regions. There are several situations where this might not be the case. If there are local labor markets and labor supply shifts differently across regions (caused, for example, by labor migration), employment and productivity growth do not necessarily covary. The change in employment growth might also be smaller than increase in labor demand if there are congestion externalities such as air pollution shifting labor supply and labor demand simultaneously. Also, if the demand for output is very inelastic in some sectors, increases in productivity may translate into a small increase in labor demand since firms become able to produce more output with the same labor, and there may be reductions in the sector’s employment in that region<sup>3</sup> . Furthermore, if in some sectors technological growth is labor biased, productivity growth may not translate into employment growth.

Ideally economists would like to have a direct measure for regional productivity growth. One approach is to estimate a regional production function and interpreting the residual as total productivity

> 1 Combes (2000) finds that sector concentration fosters employment growth only in two manufacturing sectors: Glass and Office machinery and computers.

> 2 Glaeser et al. (1992) and Henderson et al. (1995) both use data for the US and reach different conclusions. However, they analyze different time periods and the samples are constructed in different ways. In Glaeser et al. (1992) the sample includes only the six largest sectors for each city and, therefore, all sectors included have an initially high degree of concentration. Furthermore, non-manufacturing sectors such as wholesale and retail trade are heavily represented, while in Henderson et al. (1995), these are not included.

> 3 I thank Antonio Ciccone for pointing this out.

3
and North Africa, Sub-Saharan Africa and Central and Eastern Europe. With the exception of the MENA region, all emerging and developing regions have on average improved their supply-side capacity. The deterioration in the MENA region intensified since 2010. The indicators in the database also trace well the legacy on supply-side capacity and overall export performance of the double-dip recession in the euro area.

Our measure of competitiveness is correctly associated with factors that are commonly perceived as boosting competitiveness. In future work, we plan to construct the measures of export performance for broad sectors and to construct measures of export performance in volumes that also account for the extensive margin of trade. The export performance database is meant to be an instrument at the disposal of researchers, policy makers and the private sector. We hope they will use it, find it of some use and provide critical feedback, so that the database can evolve into an increasingly reliable and up-to-date source of information.

# **REFERENCES**

Amador J and S Cabral (2008), “The portuguese export performance in perspective: A constant market share analysis', _Economic Bulletin and Financial Stability Report Articles_ , Banco de Portugal.

Balassa (1965), “Trade Liberalization and Revealed Comparative Advantage”, _The Manchester School_ 33(2), 99–123.

Baunsgaard T, M Villafuerte, M Poplawski-Ribeiro, and C Richmond (2012) “Fiscal Frameworks for Resource Rich Developing Countries” IMF Staff Discussion Notes SDN/12/04.

Beltramello A, KD Backer and L Moussiegt (2012), “The export performance of countries within global value chains (gvcs)”, _OECD Working Papers_ , 2012/2.

Bowen HP and J Pelzman (1984), `Us export competitiveness: 1962-77', _Applied Economics_ 16, 461-473.

Brenton P, and R Newfarmer (2007), “Watching more than the discovery channel : export cycles and diversification in development”, _Policy Research Working Paper Series_ 4302, The World Bank.

Bricongne JC, L Fontagne, G Gaulier, D Taglioni and V Vicard (2012), “Firms and the Global Crisis: French exports in the turmoil”, _Journal of International Economics_ 87, 1 134-146.

Buckley PJ, CL Pass and K Prescott (1988), “Measures of International Competitiveness: A Critical Survey”, _Journal of Marketing Management_ 4 (2), 175-200.

Chen, R, G-M Milesi-Ferretti, and T Tressel (2012), “External Imbalances in the Euro Area”, IMF Working Paper.

Cheptea A, L Fontagne’ and S Zignago. (2012), “European Export Performance”, _Banque de France Working Paper_ 393.

Cheptea A, G Gaulier and S Zignago (2005) “World Trade Competitiveness: a Disaggregated View by Shift-Share Analysis,” _CEPII Working Paper_ 23,.

Dadush, U and B Stancil (2011), “Is the euro rescue succeeding?”, VoxEU.org, 6 February.

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