rafmacalaba/datause-encoder-data huggingface dataset:
in column (3), after controlling for unobserved time-invariant firm-specific effects and timevariant country-specific effects, the EU ETS participation in Phase 2 has no effect on employment, though Phase 1 participation shows a non-significant 10 percent decrease. Most of the effects in column (1) are absorbed into the firm fixed effects. Column (4) controls for allowances allocated and surrendered. We can see that there is a positive effect of surrendered permits on employment of Phase 1 participating firms, though that may be caused by the positive production shocks that increase both labor and pollution.

Table 10 Results on Employment for Iron and Steel

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|Phase 1 Participation|0.631***|0.0552|-0.102|-1.012**|
||(3.38)|(0.42)|(-0.60)|(-2.05)|
|Phase 2 Participation|0.441**|0.146|0.00211|-0.756|
||(2.28)|(1.29)|(0.01)|(-1.08)|
|Phase 1×Log(Surrendered)||||0.0803*<br>(1.70)|
|Phase 2×Log(Surrendered)||||-0.00854<br>(-0.10)|
|Phase 1×Log(Allocated)||||0.000179<br>(0.01)|
|Phase 2×Log(Allocated)||||0.0743<br>(0.79)|
|Plant Fixed Effects|No|Yes|Yes|Yes|
|Country-by-Year Fixed Effects|No|No|Yes|Yes|
|Observations|902|902|902|902|
|Adjusted_R_<sup>_2_</sup>|0.029|0.002|0.003|0.002|

Note: Dependent variable is the logarithm of number of employees. Standard errors are clustered at the firm level and t statistics are shown in the respective parentheses. *, **, and *** indicate significance at the 10, 5, and 1 percent levels Table 11 tabulates the results for unit material cost. The OLS result in column (1) shows that there are no statistically significant relationship between EU ETS participation and unit material cost. The fixed effects model in column (2) implies the Phase 1 of EU ETS increases the unit material cost of steel plants by about 4.3 percent. However, after controlling for possible policy responses by participating countries, the effect decreases to around 2.5 percent and it is no longer statistically significant. In both cases, Phase 1 appears to have no impact on the iron and steel plants– before and after controlling for the country-by-year dummies, Phase 1 participation 20
|Youth literacy rate (% of people ages 15-24)|69.1|n.d.|74.6|
|---|---|---|---|
|Life expectancy at birth (years)|42.3|45.3|47.8|
|Under-5 mortality rate (per 1,000 live births)|149.6|133.2|111.0|
|Maternal mortality rate (per 100,000 live births)|600.0|560.0|470.0|
|Prevalence of HIV (% of population ages 15-49)|14.2|13.8|13.5|
|Headcount Poverty ratio (% of population)|n.d.|59.3|n.d.|

_Source: World Bank World Development Indicators._ Aside from simple growth, fiscal policy is one of the main tools to promote economic equity and reduce poverty. Goñi, Lopez, and Serven (2008) demonstrate the redistributive potential of fiscal policy. They show that the difference in income inequality between Latin America (the most unequal region in the world) and Western Europe (the most equal region) is striking only after taxes and transfers are taken into account.<sup>2</sup> In Sub-Saharan Africa, Sahn and Younger (2000) conclude that even though social spending is progressive, it is not pro-poor because social services and other public expenditures disproportionately benefit the wealthy.<sup>3</sup> Similarly, analyses of Zambian public expenditures do not support the notion of a deliberate equalization policy. Giugale, Narayan and Saavedra (2011) show that greater equality in children‘s access to key services, such as education and immunization, are mostly explained by a scale effect, that is, an expansion of service coverage rather than the more equitable distribution of the service.

At the sector level, recent evidence (see Cuesta and Martinez-Vazquez [2012]) shows that not every fiscal tool has the same distributive impact: primary and secondary education spending and income taxation are found to be generally progressive, while tertiary education, curative health care, energy subsidies, and indirect taxes are by and large regressive. However, the redistributive impacts of fiscal policy are not universal, and large differences are observed across countries. For example, Breceda, Rigolini, and Saavedra‘s (2009) benefit -incidence analysis of key social spending and revenue sources highlights notable differences in the degree of progressiveness of fiscal policy between Honduras and Colombia in the Latin America region and between the United States and the United Kingdom among OECD countries.

> 2 The Euro-15 Gini coefficient drops from 0.45 to 0.35 when social spending and taxes are added to the initial distribution of incomes. For Latin America–6 (Argentina, Brazil, Chile, Colombia, Mexico, and Peru), the Gini coefficient falls only slightly from 0.49 to 0.47.

> 3 By contrast, a host of literature (see Fiszbein and Schady 2009) has shown substantive redistributive social impacts from welltargeted conditional cash transfers (CCTs) at a relatively low fiscal cost, between 0.5 and 1 percent of GDP.

3
# **3.2. What is the impact of foreign bank participation in developing countries?**

# **_(i) Competition & Efficiency_**

The promises of efficiency improvements and greater competition in the banking sector are perhaps the main arguments brought forth by proponents of foreign bank entry. As detailed below, with the exception of research that focuses on Latin America where the evidence is mixed, existing studies on the impact of foreign bank participation on efficiency and competition largely support the claim that foreign banks operating in developing countries are more efficient than domestic banks (i.e., have lower overhead costs), charge lower spreads, and help promote bank competition by pressuring other banks to lower their costs and their spreads.

Claessens, Demirguc-Kunt and Huizinga (2001), Claessens and Lee (2003), and Claessens and Laeven (2003) offer cross-country evidence on the benefits of foreign bank participation in terms of efficiency gains and greater competition. Using data for 80 countries from 1995 to 1998, Claessens, Demirguc-Kunt and Huizinga (2001) find that foreign bank participation is associated with a reduction in profitability, non-interest income and overhead expenses of domestic banks – results which they interpret as indications of greater efficiency and competition due to foreign bank participation. In a follow-up paper, Claessens and Lee (2003) focus on financial systems in 58 low-income countries. They find that the increased presence of foreign banks benefited the local banking sector by reducing financial intermediation costs making the banking system more efficient and robust. Following the Panzar and Rose (1987) methodology to obtain a parameter that quantifies the degree of competition in the banking sector in 50 countries between 1994 and 2001, Claessens and Laeven (2003) find that systems with greater foreign bank entry and with fewer activity and entry restrictions are more competitive.

A variety of country and regional case studies complement the cross-country literature on the impact of foreign bank participation on efficiency and competition. Using bank accounting data from Philippines for 1990-98, Unite and Sullivan (2002) investigate how foreign bank entry and increased foreign ownership of banks in that country affected bank efficiency and competition. The authors find that greater foreign bank entry reduced the interest rates and operating expenses of domestic banks, but not their profitability. They conclude that foreign competition forced domestic banks to be more efficient. Denizer (2000) studies the impact of 10
spatial integration using the multivariate Johansen approach to test for co-integration of the regional price series and explore the dynamics of the price transmission process. Then, they extract the trace statistic (the test statistic for the null of no co-integration) obtained from that first stage procedure and use it as a measure of market integration. The larger the value of that statistic, the stronger is the evidence for market integration. In the second stage, the authors regress the trace on measures of government intervention (purchases and sales of rice carried out by Bulog in each market), infrastructure (road density), market development (income per capita of the region) and a dummy that controls for the periods of self-sufficiency in rice production. The results for the whole period suggest that only the purchases of rice by Bulog had a significant effect on market integration. The rest of the variables do not significantly explain it. For the self-sufficiency period, sales of rice by Bulog also has a significantly positive effect, as well as per capita income.

Summarizing, there is scarce literature exploring determinants of market integration. Probably the most robust lesson that has been learnt is that spatial integration is weaker in distant provinces, and stronger in central ones. This paper attempts to contribute to this scarce literature by tackling the question of what are the factors that determine market integration in the context of Indonesian commodity markets.

# **C. DATASET: REVIEW AND DESCRIPTIVE STATISTICS**

In this paper we use consumer price time series for the period January 1993 − December 2007 for rice, sugar and cooking oil, and producer price time series for the period January 1992 − December 2006 for soybeans and maize. All price series were obtained from the National Bureau of Statistics of Indonesia (BPS). Data were also obtained from CEIC (CEIC Data Company Ltd) and BPS.

Table 2 presents mean, standard deviation, maximum and minimum of each of the variables used in this analysis, across provinces. „Distance‟ is the minimum distance in kilometers to 6
# **4. Micro-level indicators shedding light on Brazil’s closedness**

A more interesting perspective on Brazil’s lack of trade openness can be obtained from looking at the number and characteristics of exporting firms.

The first result is that very few Brazilian firms export (World Bank, 2014). The share of exporters among all formal sector firms is less than 0.5 percent. Indeed, the absolute number of exporters in Brazil

- less than 20,000 – is roughly the same as that of Norway; a country of just over 5 million people compared to Brazil’s 200 million. This means that, while in Norway there is one exporting firm for about every 250 Norwegians, the ratio in Brazil is one for every 10,000 Brazilians.

Of course, Norway and Brazil are vastly different countries. Norway’s is one of the richest countries in the world; its GDP per capita is almost 10 times that of Brazil. Norway’s total GDP is about a quarter of Brazil’s, indicating that Norway can be more aptly be described as a small open economy. Norway is also a small country close to and well connected with many more countries in its region compared to Brazil. On the other hand, Norway is also a commodity exporter, with the petroleum sector accounting for more than half of total exports. In the case of Norway, a strong natural resource sector appears to coexist with value chain integration and dynamic exporters in other sectors.

Looking at a larger set of countries, we observe that Brazil is indeed an outlier. Brazil’s number of exporters relative to the population is low even when controlling for GDP per capita (Figure 5).

7
significant correlation if the regression is made with the average GDP growth (Table 4). Nevertheless, this study focuses on the per capita GDP growth rate, which regression does not show any significant results, even less by excluding Mexico City, which is the clear statistical outlier of the sample.

**Figure 7: Correlation between average corruption and average growth (left) and average per capita growth (right), 2001-2005.**

|0.00<br>0.01<br>0.02<br>0.03<br>0.04<br>0.05<br>avg growth 2001-05||-001<br>0.00<br>0.01<br>0.02<br>0.03<br>0.04<br>avg per capita growth 2001-05<br>Mexico<br>City|
|---|---|---|
|0|5<br>10<br>15<br>20<br>avg corruption 2001-05|.<br>0<br>5<br>10<br>15<br>20<br>avg corruption 2001-05|
|**Table 4:**<br>**Average gro**|**Regression results with Corruptio**<br>**wth 2001-05**|**n (average 2001-05) as independent variable**<br>**Average growth per capita 2001-05**|
||Allstates<br>w/oMexico City|Allstates<br>w/oMexico City|
|Coefficient<br>_t_-statistic|-0.0016943<br>-0.0014455<br>-4.00<br>-2.45|Coefficient<br>-0.0003203<br>0.0000971<br>_t_-statistic<br>-0.70<br>0.16|
|_p_-value|0.000<br>0.021|_p_-value<br>0.487<br>0.873|
|R<sup>2</sup>|0.1998<br>0.1029|R<sup>2</sup><br>0.0088<br>0.0005|

All regressions are adjusted with a robust estimator

# **a.3. Control variables**

We extend the analysis to study whether the lack of significance between corruption and per capita growth remains by adding control variables, following Chiquiar (2005) for Mexico and numerous contributors to the cross-country growth regression literature. All variables included in this model are per Mexican state. This group of variables includes: i) _initial GDP per capita_ , as suggested by the papers of Mauro (1995) and Barro (1996); ii) _distance to the U.S. border_ , a variable much discussed in growth analytics for the specific case of Mexico, where exports to the United States account for 85 percent of the total Mexican exports. It is measured by the distance from the capitals of each Mexican state to the northern border; iii) _average schooling years_ and _students per teacher_ , assuming the hypothesis that education promotes growth; iv) _road density_ and _share of_ 14
would appear to have an enormous gender disparity of 2. It hardly seems right that medical progress that leads to better survival chances be called an increase in gender disparity.

A second possibility is to norm to recent mortality rates in a richer, low mortality country. This represents the mortality when medical resources are effective and plentiful, which might represent "natural" mortality. As Svedberg points out, in one setting where medical technology is as advanced as possible (Sweden in the 1980s), "the child mortality rates are almost identical [for boys and girls], .29 and .28 respectively" (Svedberg, 1990, fn. 3). But this is not always the case. In the U.S., the death rate in ages 1 to 4 is .52 for boys and .41 for girls, so the gender ratio is .78. Hence, a country with equal male and female death rates normed to the U.S. ratios would have a gender disparity of 1.27. However, 62 percent of the gender difference in mortality is due to a greater frequency of accidental death from accidents, as the gender mortality ratio for accidents is .68 versus .86 for all other causes of death. If a country with equal death rates were normed to the U.S. death rates from nonaccidental causes alone, the gender disparity would be 1.15. It seems extremely odd to argue that the reported gender disparity for a country with gender equal death rates should be so strongly influenced by the propensity of a reference population of U.S. boys to die of fatal accidents.

_Results._ The recent exchange between Svedberg and Klasen (Svedberg, 1990, 1996, Klasen, 1996) highlights the potential importance of normalizing. When normalizing mortality rates using the Northern European countries from 1820-1963 as the reference, Klasen finds that within Sub-Saharan Africa DHS samples, nine out of 14 countries exhibit excess female child mortality. Using a collection of 32 surveys from 20 countries compiled by Svedberg, he 23
Policy Research Working Paper 5590

# **Abstract**

A long empirical literature has examined the idea that, in the absence of hedging mechanisms, currency risk should have an adverse effect on the export volumes of risk averse exporters. But there are no clear conclusions from this literature, and the current consensus seems to be that there is at most a weak negative effect of exchange rate volatility on aggregate trade flows. However, most of this literature examines the impact of exchange rate volatility on aggregate trade flows, implicitly assuming a uniform impact of this volatility on exporters across sectors. This paper explots the fact that, if exchange rate volatility is detrimental for trade, firms exporting goods that offer a natural hedge against exchange rate fluctuations—i.e.

those whose international price is negatively correlated with the nominal exchange rate of the country where they operate—should be relatively benefited in environments of high exchange rate volatility, and capture a larger share of the country’s export basket. This hypothesis is tested using detailed data on the composition of trade of 132 countries at 4-digit SITC level. The results show that the commodities that offer natural hedge capture a larger share of a country’s export basket when the exchange rate is volatile, but there is only weak evidence that the availability of financial derivatives to hedge currency risk reduces the importance of a sector’s natural hedge.

This paper is a product of the Macroeconomics and Growth Team, Development Research Group. 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://econ.worldbank.org. The author may be contacted at craddatz@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
The sample includes 6 countries that are high-income countries, namely Germany (Eastern after re-unification), Greece, Ireland, Portugal, Spain, and Korea. It includes 13 countries from LAC, 9 from Europe and Central Asia (ECA), 4 from East Asia and the Pacific (EAP) including China, 3 African countries, plus Egypt. Clearly, this sample, which is used for econometric analysis, is not representative across all regions of the world. However, the sample of firms might be representative of manufacturing firms from around the world, especially from developing countries. Since this might not be true, some of the relevant regressions use weights, based on each country’s labor force (i.e., population aged 15-64 years). This is reasonable if the number of firms from each country is proportional to the labor force in each.

Regarding the incidence of firms innovating via the introduction of a new product, the data show a wide range of country experiences, ranging from 15 percent of Chinese and Egyptian firms to 75 percent in Argentina. It is noteworthy that the percentages for the richer countries in the sample are not above the overall sample average of 43 percent. But LAC’s average is above the sample average.

In most countries, a large share of firms that reported new products also report R&D expenditures. In the total sample, 60 percent of firms with product innovation also report R&D, whereas only 15 percent of non-innovative firms report some R&D expenditures. This pattern holds for most countries individually for R&D, licensing, export status, and foreign ownership. China is the only exception. In this country, the percentage of non-innovative firms that report R&D expenditures, licensing payments, exporting, and foreign ownership is higher than among the innovative firms.<sup>6</sup> Although the high correlation between innovation and the other firm characteristics is expected, it is clear that identifying the partial correlations between the propensity to introduce a new product and the other firm characteristics is important since high correlations among all the firm-level characteristics are also expected.

There is no clear relationship between trade policies and the share of innovative firms across countries, however. For example, Argentina appears with 75 percent of firms being innovative, but it also utilizes numerous non-tariff barriers (NTBs) covering, on average across

> 6 The data for China is consistent with product-level export data that suggests that mainland China introduced comparatively few new export products during 1994-2003 (Klinger and Lederman 2006).

10
Information Technology and Provision of National Identification Cards by the Bolivian Police: Evidence from Two Randomized Natural Field Experiments<sup>*</sup> _Alberto Chong Gustavo Machicado Salas Monica Yanez-Pagans_ JEL Classifications: C93, O38, J24

> * Yanez-Pagans: The World Bank (E-mail: myanezpagans@worldbank.org). Machicado Salas: Institute for Advanced Development Studies (E-mail: cmachicado@inesad.edu.bo). We are very grateful to V ́ıctor Hugo Escobar, Alfonso Vargas, Wilhelm Taboada, and Boris Villarroel for their collaboration in making this study possible. For helpful discussions and comments, we thank Horacio Aguirre, Mary Arends-Kuenning, Kathy Baylis, Nestor Gandelman, Nicol ́as Garcette, Saweda Liverpool, Ghazala Mansuri, Nolan Miller, Hernan Winkler, Alex Winter-Nelson, and Patricia Yanez-Pagans. This project was funded and undertaken as part of the Latin American and Caribbean Research Network of the InterAmerican Development Bank. The paper has been screened to insure that no confidential information is revealed.
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