rafmacalaba/data-use-mentions-extended huggingface dataset:
br>per worker|IDN exports<br>per worker|IDN exports<br>per worker|IDN exports<br>per worker *<br>ICT|
||(1)|(2)|(3)|(4)|
|Global demand for foreign products|0.000341<br>(0.000)***|0.000342<br>(0.000)***|0.000385<br>(0.000)***|-0.000145<br>(0.000)***|
|Global demand for foreign products *|||-0.000305|0.00113|
|Share of hhlds with computer|||(0.000352)|(0.000101)***|
|ICT at the province level|No|Yes|Yes|Yes|
|Province level controls|Yes|Yes|Yes|Yes|
|Industry level controls|Yes|Yes|Yes|Yes|
|Province, industry and year FE|Yes|Yes|Yes|Yes|
|Observations|2,734|2,734|2,734|2,734|
|R-squared|0.983|0.983|0.983|0.946|
|F-stat|56.91|56.90|34.25|69.90|

Source: Authors’ calculations based on Sakernas 2005-2010 and 2011-2015, Susenas 2005-2010 and 2011-2015, and UN Comtrade database 2005-2010 and 2011-2015.

Notes: OLS regressions. Indonesian exports per worker in thousands of USD at 2010 prices and global demand for foreign products in millions of USD at 2010 prices. ICT variable at the province level is the share of households with computer. Province level controls include the age structure of the population, the share of urban population, real GDP per capita, and the minimum wage level. Industry level controls include the gender and educational composition of
# **1 Introduction**

A growing literature has focused on the misallocation of resources in order to answer why some countries are poorer and have lower productivity levels.<sup>1,2</sup> Guner _et al._ (2008) identify size-dependent policies as one of the direct sources of misallocation. The size-dependent policies favor small establishments and levy higher regulations or taxes on bigger establishments. In this paper, I study the relationship between size-dependent distortions and economic development in the presence of bribery opportunities.

I define bribery as a transfer from a private party to government officials in order to ‘get things done’. These ‘things’ can include acquiring valuable licenses and permits to operate or avoiding taxes. In this paper, I ask and quantitatively answer the following questions: What is the inferred magnitude of distortions when a model is disciplined to account for the plant size distribution and bribery data? What are the aggregate consequences of an increase in the size dependency of the distortions under the presence of bribery opportunities? Finally, how large are the possible gains from removing the distortions with and without the bribery opportunities? These questions have not been answered by the previous literature, even though bribery is prevalent among developing countries. Answers to these questions provide a better understanding of the relationship between bribery, plant size distribution, GDP per capita, and the effects of various policies, such as removing the bribery mechanism and distortions in an economy.

First, I document the facts related to bribery and the plant size distribution in a typical developing country, Türkiye. Choosing this country does not imply particularly large levels of bribery and size dependent distortions compared to other countries. I use Turkish data as an example because the bribery spending data for different size groups as well as the plant size distribution data are available for Türkiye. Using representative, plant-level data from the World Bank’s Enterprise Surveys (WBES), I show that while bigger enterprises pay higher bribes, they spend a lower fraction of their value added (
the city is an indication of economic growth (Boserup 1970:174). A survey of migration in Indonesia has concluded that migration has been dominated by men and that women are either following their husband or are avoiding economic hardship in their home town (Khoo, 1986:6). However, it has also been noted that there is an inclination for women to move to another place, especially to Jakarta, by themselves. Hugo (1989:215) finds that there are more women moving to Jakarta than men, whereas the traditional pattern of more men than women migration prevails in Lampung.

Several studies indicate that the majority of migrants are young, between the ages of 1525 years old (Todaro 1976). This general trend probably holds true for Indonesia as indicated by a survey on the pattern of migration to Pasar Rebo district in Jakarta, 28 per cent of the people are 15-19 years old (Aswatini 1986). People who are not married are also more inclined to move
, there is an "improved" category. The concept of improved source of drinking water and improved sanitation facility was proposed by the WHO and UNICEF in 2004 and implemented in the DHS 2008. An attempt was made to approximate the "improved" categories in the DHS 2003 data (KNBS and ICF Macro 2010). In order to obtain time-consistent water and sanitation variables, we slightly diverge from the categorization of improved water source and sanitation proposed in the Kenya DHS 2008 report. A total of 112 observations are excluded from the analysis due to a missing value on water and sanitation quality, which is caused by the mother not being a de jure resident of the household.
Preiß, C. (2020). Information and communication technology in the lives of forcibly displaced persons in Kenya. _Discussion Paper, 15/2020_ .

- Hamilton, Z., Casswell, J., & Alonso, A. (2020). _The digital lives of refugees and Kenyans with disabilities in Nairobi: A human-centred design approach to identifying mobileenabled opportunities._ London: GSM Association.

- Egger, D., Miguel, E., Warren, S. S., Shenoy, A., Collins, E., Karlan, D., . . . et al. (2021). Falling living standards during the COVID-19 crisis: Quantitative evidence from nine developing countries. _Science Advances, 7_ (6).

- Janssens, W., Pradhan, M., Groot, R. d., Sidze, E., Pythagore, H., Donfouet, P., & Abajobir, A. (2021). The short-term economic effects of COVID-19 on low-income households in rural Kenya: An analysis using weekly financial household data. _World Development, 138_ .

- Kansiime, M. K., Tambo, J. A., Mugambi, I., Bundi, M., Kara, A., & Owuor, C. (2021). COVID19 implications on household income and food security in Kenya and Uganda: Findings from a rapid assessment. _World Development, 137_ .

- Depetris-Chauvin, E., & Santos, R. J. (2018). Unexpected guests: The impact of internal displacement inflows on rental prices in Colombian host cities. _Journal of Development Economics, 134_ , 289–309.

- Maystadt, J.-F., & Duranton, G. (2019). The development push of refugees: Evidence from Tanzania. _Journal of Economic Geography, 19_ (2), 299-334.

- FAO. (2020). _Impact of COVID-19 on informal workers._ Food and Agriculture Organization of the United Nations.

- KNBS
Cole, Matthew A., and Anthony J. Rayner. 2000. ―The Uruguay Round and Air Pollution: Estimating the Composition, Scale, and Technique Effects of Trade Liberalization.‖ _Journal of International Trade and Economic Development_ 9 (3, September): 339–54.

Copeland, Brian R., and M. Scott Taylor. 1994. ―North-South Trade and the Environment.‖ _Quarterly Journal of Economics_ 109 (3, August): 755–87.

———.2003. _International Trade and Environment: Theory and Practice_ . Princeton, NJ: Princeton University Press.

———. 2004. ―Trade, Growth, and the Environment.‖ _Journal of Economic Literature_ 42 (1, March): 7– 71.

Dean, Judith M. 2002. ―Does Trade Liberalization Harm the Environment? A New Test.‖ _Canadian Journal of Economics_ 35 (4, November): 819–42.

de Bruyn, S. M., J. C. J. M. van den Bergh, and J. B. Opschoor. 1998 _._ ―Economic Growth and Emissions: Reconsidering the Empirical Basis of Environmental Kuznets Curves.‖ _Ecological Economics_ 25 (2, May): 161–75.

Di Maria, Corrado, and Sjak A. Smulders. 2004. ―Trade Pessimists vs. Technology Optimists: Induced Technical Change and Pollution Havens.‖ Open Access Publication urn:hdl:10197/845, University College Dublin.

Dijkgraaf, Elbert, and Herman Vollebergh. 2004. ―A Note on Testing for Environmental Kuznets Curves with Panel Data.‖ Others 0409001, EconWPA.Washington University, St. Louis.

Egli, Hannes. 2004. ―The Environmental Kuznets Curve: Evidence from Time Series Data for Germany,‖ CER-ETH Economics Working Paper 03/28, Center of Economic Research, Swiss Federal Institute of Technology (ETH), Zurich.

Esty, D., and M. Porter. 2005. ―National Environmental Performance: An Empirical
the obtained efficiency scores provide a more adequate picture of revenue mobilization potential in developing countries. In addition, we estimate a second frontier based exclusively on the set of lowincome countries (LICs) in our data set. The purpose of this second frontier is to provide an upper bound estimate of the efficiency scores for LICs. In particular, the second frontier assumes that LICs can generate the same revenue levels as other LICs with comparable economic conditions (as captured by the DEA input index) but not necessarily the revenue levels achieved by lower-middle income countries (LMICs) and upper-middle income countries (UMICs) with such conditions, thus accounting for the special challenges to revenue mobilization facing many LICs.

It should be noted that the results derived from DEA are subject to the following limitations. Given that DEA is a non-parametric method of estimating efficiency scores, the derived results are of a descriptive nature and should not be interpreted as identifying causal links between the included variables. Instead, the performed DEA compares revenues among a set of countries at a given time and identifies those countries that, relative to others with similar economic conditions, are currently performing below the level which they should potentially be able to. This also implies that the analysis is based exclusively on current conditions and thus not designed to provide forecasts of revenues under possible scenarios of future changes in economic or other conditions. Finally, it should be noted that the obtained results relate only to the considered outcome in government revenues relative to GDP and do not provide direct implications for potential welfare gains (or losses) associated with increased revenues.

# _B. Panel Regression Analysis_

To investigate the factors that potentially account for variation in efficiency scores across countries, we estimate a panel regression framework using the obtained DEA efficiency scores as dependent variable. The purpose of this analysis is to examine which factors are associated with higher or lower relative performance in achieving domestic revenue potential (as captured by the DEA scores), i.e., why some countries generate more revenues than other countries with comparable
in values (thousands of US dollars) and quantities.<sup>13</sup> Trade data at the HS 6-digit level allows us to account for export failures at a detailed product level which would otherwise be undetected when using more aggregated industry data. In our estimations, we focus on the manufacturing exports to the United States during the 1995-2011 period.<sup>14</sup> The three time-varying variables (initial export, total export, number of suppliers) are measured at the beginning of the export spell. The terms ‘given year’ or ‘time’ thus refer to the initial year of a given export spell. _Initial export_ is measured at the productcountry-time level and represents the export value of a given product exported by a given country to the US market in the initial year of exporting. The variable captures the levels of mutual trust and expectations about the potential future exports that exist among the trade partners at the beginning of a new trade relationship. _Total export_ is measured at the product-country-time level and represents the overall value of the country’s exports of a given product to the world market in a given year. It serves as a proxy for the size and overall export performance of a given exporting country in that given product. _Number of suppliers_ is measured at the product-time level and counts the number of countries that export a given product in a given year to the United States. The variable can represent both the level of competition and the potential market size for a given product in the US destination market.

A dummy variable called _Multiple spell_ is measured at the product-country level. It equals one if a given country exports a given product to the United States during two or more separate export spells, identifying instances when the country at some point stops exporting a product but later re-enters the US market with the same product again. The inclusion of this variable accounts for the possibility that repeated exits and re-entries into exporting of the same product to the same destination might affect this product’s
# **Box 0.1: Overview of data collection templates**

There are a total of 11 templates to be completed as follows:

# **Pre-field**

- Template 1: Jurisdictional responsibilities in infrastructure service delivery

- Template 2: Special funds financing infrastructure service delivery

- Template 3: Private participation in infrastructure

- Template 4: Official development assistance (ODA) in infrastructure service delivery

# **Qualitative**

- Template 5: Basic budgetary institutions

- Template 6: Budgetary cycle diagram

- Template 7: Governance of public operators (one for each public enterprise and special fund)

# **Quantitative**

- Template 8: Macroeconomic parameters for normalization

- Template 9: Macroeconomic parameters for budgetary context of infrastructure spending

- Template 10: Functional and economic classification of government expenses (separate versions will be needed for (i) central versus local government; (ii) each year of data collection; (iii) budget estimates, releases and actual; (iv) capital and recurring expenditures for countries with dual budgeting)

- Template 11: Public operators’ financial data (one for each public enterprise and special fund).

As a companion to this Guide, the templates are all available in Microsoft Excel format to facilitate the data collection and can be downloaded from: <u>www.infrastructureafrica.org.</u> <u>Source: Author’s elaboration.</u> 12
the capacity of aid to treat equal countries equally. And transparency regards the capacity to assess the equity and effectiveness of aid. In a recent note, Anderson and Waddington (2006) group contributions to the normative debate into three main allocation principles respectively based on: poverty-efficiency, equal opportunity or structural indicators, roughly reflecting in this way the broader norms described.

The poverty-efficiency literature emphasizes the importance of considering the poverty level in conjunction with the policy capacity of a country so as to maximize the poverty reduction capacity of aid at the global level given a budget constraint. Collier and Dollar (2001) and Collier and Dollar (2002), for example, promote a poverty-efficiency aid allocation criteria. Poverty being equal, aid should increase with the policy capacity of a country, because aid can have larger growth effect in a better policy environment. Vice-versa, the policy capacity being equal, aid should increase with the level of poverty because the growthpromoting effect of aid has more poverty reduction capacity in a very poor country. The poverty-efficiency position is supported by influential institutions such as the World Bank (Wolfensohn, Stern, Goldin, Rogers, and Karlsson, 2002) or the OECD (OECD, 2003; OECD, 2006) although empirical evidence (among others, Nunnenkamp and Thiele, 2006) suggests that the broader donors’ community rarely follows this criterion.

This position is also questioned by scholars arguing for transparency, who point out the necessity of predictable, or less volatile, flows of aid to individual countries (among others Eifert and Gelb, 2008, Fielding and Mavrotas, 2008, Bulir and Hamann, 2006, Bulir and Hamann, 2003). As the policy capacity of a country is hard to assess and also volatile, the poverty efficiency criteria would be difficult to implement and also subject to frequent changes. This would speak in favor of using standard statistics such as GDP per capita or poverty rates to rank countries and allocate aid so as to capture basic but well understood indicators. Guillaumont, 2008 argues that the poverty-efficiency
a global panel including LAC, finds only weak and borderline significant effects.  One key transmission mechanism, an increased wage elasticity of labor driven by higher product elasticities, has not materialized in Colombia or Chile and shows only fragile appearance in Mexico (Fajnzylber and Maloney, forthcoming).  Further, extracting the permanent component of worker income variance in the Mexican urban labor survey, Krebs, Krishna and Maloney (2004) find no increase in the permanent component of risk, but a transitory increase corresponding to the adjustment period.

In sum, there are transitory impacts of trade liberalization, but openness does not appear correlated with many of the expected evils. There is actually surprising low reallocation after liberalization, no permanent changes in unemployment, mixed impacts on wages in the medium term, an expansion of the wage gap, and overall increased job quality in exporting and import competing industries.

# **Further work**

- **<u>Measurement of labor market outcomes:</u>** There is some concern about lack of crosscountry comparability of labor market indicators.  It may be that Mexico’s consistently lower unemployment rates reflect a better functioning labor market than, say than that of Argentina with much higher secular levels, or it may perhaps reflect measurement differences, including those arising from how workers approach the standard survey questions.

- **<u>Complementary policies:</u>** Recent work in the region, particularly on NAFTA, increasingly stresses that trade reform offers opportunities, but it is not a panacea that obviates reforms in other areas.  Exposure to international competition may make certain labor market distortions more critical, but as yet there is little work studying the necessary complementary policies in the areas of legislation, collective bargaining, skill accumulation, and active labor market policies.  It goes without saying that raising the

4
In the first stage, we regress the level of banking sector development— proxied by the number of commercial bank branches per 100,000 adults— in country _i_ and year _t_ against three variants of banking sector development in other (neighboring) countries _(_ Branches−it−iiii∗ ) _:_ (i) the unweighted average of the number of bank branches in all countries with common borders to country _i_ , (ii) the geographic distance-discounted average of the number of bank branches in all countries in the same region excluding country _i_ , and (iii) the geographic distance-discounted average of the number of bank branches in all countries excluding country _i_ .<sup>10</sup> The three variants of our instrumental variable both capture foreign financial development as well as the fact that the link between domestic and foreign financial sector development is stronger for neighboring countries. Both the regional and global distance-discounted averages are defined in this equation: The proxy for geographic proximity (i.e., geodesic distance) is obtained from the CEPII database. Common regions are defined as in World Bank (2021). In both the first and second-stage regressions, we control for the same set of control variables as in equation (1), including the level of per capita income (in 2010 U.S. dollars) and the three institutional quality measures taken from WGI (i.e., control of corruption, regulatory quality, and rule of law). All regressions include year fixed effects (yt) and country fixed effects (ci).

Table 4 shows the results of the first-stage regression for an unconstrained sample for 2004-2018 (some of these observations will be dropped for the full estimation due to the lack of data on informal activity). Banking sector development in country _i_ is significantly positively correlated with banking sector development in countries that are geographically close or in the same region. This supports our hypothesis that a well-developed banking system in one country “spills over” into a better developed banking
.

- Landry, Pierre F., Xiaobo Lü, and Haiyan Duan. 2017. “Does Performance Matter? Evaluating Political Selection Along the Chinese Administrative Ladder.” _Comparative Political Studies_ 51 (8): 1074– 1105.

- Li, Hongbin and Li-An Zhou. 2005. “Political Turnover and Economic Performance: The Incentive Role of Personnel Control in China.” _Journal of Public Economics_ 89 (9-10): 1743–1762.

- Li, Xing, Chong Liu, Xi Weng, and Li-An Zhou. 2019. “Target Setting in Tournaments: Theory and Evidence from China.” _Economic Journal_ 129 (623): 2888–2915.

- Liu, Zhifeng, Chunyang He, Qiaofeng Zhang, Qingxu Huang, and Yang Yang. 2012. “Extracting the Dynamics of Urban Expansion in China Using DMSP-OLS Nighttime Light Data from 1992 to 2008.” _Landscape and Urban Planning_ 106 (1): 62–72.

- Lyu, Changjiang, Kemin Wang, Frank Zhang, and Xin Zhang. 2018. “GDP Management to Meet or Beat

33
Pension Fund along with pension, hence people have difficulty in recalling it. The latter are difficult to detect because the discounts are included in the payment due on utility bills. Regarding birth grants and childcare allowances up to 1.5 years, the number of recipients seems to be under-simulated by 50–60 percent, which may be due to underrepresentation in the sample of families with young children. Families with 3 children are few in general, and they seem to be underrepresented as well. For the means-tested benefits, a good match is achieved by calibrating the take-up rates with administrative data. The receipt of maternity capital matches the external number quite well.

**Table A-5. Programs included but not simulated in RUSMOD, number of recipients/payers (in thousands), 2017**

||RUSMOD|External|Ratio|
|---|---|---|---|
|**Benefits**||||
|Public pensions|53,826|45,182|1.19|
|Unemployment benefit|1,413|848|1.67|
|Scholarships|2,329|||
|Monthly cash payment|11,279|26,154|0.43|
|Categorical benefits for housing/utilities|17,536|36,688|0.48|
|**Taxes and Social Insurance contributions**||||
|Property and vehicle taxes|5,914|||
|Social allowance onpersonal income tax|868|||

Source: Rosstat and RUSMOD for 2017 policy year and 2016 RLMS-HSE data

**Table A-6. Programs simulated in RUSMOD, number of recipients/payers (in thousands), 2017**

||RUSMOD|RLMS-<br>HSE|Ratio|External|Ratio|
|---|---|---|---|---|---|
|**Benefits**||