rafmacalaba/datause-encoder-data huggingface dataset:
Table 7 shows the regression results for equation 8. The coefficients on all performance measures are significant at the 1% level. As expected, traders perform better than non-traders. In addition to being larger and more productive, they pay higher wages, invest more intensively, hire more non-production workers, and grow faster than non-traders. Among traders, two-way traders are the best performers. The results of Table 7 reveal analytical results of the model introduced above. Efficient producers self-select into foreign markets and among those only the most efficient ones can enter in both markets. This is because only those firms can overcome the sunk costs of entry into both markets. An important result of this estimation is that estimating export premium without controlling for import status is likely to overestimate the actual value by capturing the import premium.

In their performance rankings, two-way traders are followed by only-exporters. The lowest premium is observed in only-importers. This difference in the premiums might be due to higher sunk costs of exporting relative to importing. Hence the threshold productivity level is higher for exporting. It might also be due to low substitutability of foreign intermediate inputs with domestic inputs. Although it is difficult to determine what derives higher performance of trading firms from this descriptive analysis, the results are in accordance with several recent studies. In two studies that use the same grouping of firms with respect to their foreign exposure, Vogel and Wagner (2008) derive a similar conclusion for West and East Germany manufacturers. Using data from Belgium manufacturers, Muuls and Pisu (2007) also find similar results except only importers rank higher than only exporters in their analysis.

I also perform this descriptive analysis using the panel data for robustness. In these regressions, in order to control for reverse causality, the dependent variable at time ( _t_ ) is regressed on the trading status of firms at time ( _t-3_ ). In the growth rate regressions, I also use the values for the size of the firm at (t-3)<sup>14</sup> . The results are presented in Table 17 in the Appendix. The results of the panel regressions support the results presented in Table 7. The advantage of traders in size is more pronounced in the panel regressions. For the growth rates, only two-way traders grow significantly higher than non-traders for sales and productivity but for employment growth the picture is similar to the main regression results.

# **5 Empirical Model**

Based on the theoretical model presented above, in this section I provide a detailed reduced form analysis of whether participating in international markets is related to the heterogeneity in firm

> 14 These size values are from the surveys conducted at time ( _t-3_ ) not the retro respective values from the surveys conducted at ( _t_ ).

16
Note: Z-scores are calculated based on the entire Enterprise Survey sample. Corporate ESG _weighted_ : 40% for E, 25% for S, 35% for G. Source: Authors’ calculations based on Enterprise Survey data.

MENA countries’ social component score, on the other hand, is the lowest among all regions. The gender subcomponent – which, together with education and training of the workforce, is determining the S component – is particularly weak. Female participation in the workforce in MENA countries is low: the share of female workers in MENA (considering the firms that are part of the Enterprise Survey) is 25%, significantly lower than in the other areas (apart from Turkey). The female representation in management is poor: only 5% of MENA firms have females in management, while this ratio is more than 20% in Russia, Central and Eastern Europe and Central Asia. At the country level, Morocco and Tunisia have more female participation in the workforce (higher than 30% of total workforce in the Enterprise Survey sample) and Tunisia has a better performance in terms of presence of female management as well (10% of the firms). In this respect, the West Bank and Gaza and Jordan have the lowest presence of females in management (1% and 3% of firms respectively), with Lebanon, Morocco and Egypt around 5%6%.

**Figure 10 – Female participation** (percentage on total)

<!-- Start of picture text --> 50%<br>Firms with female in<br>management<br>40% Share of female<br>workers<br>30%<br>20%<br>10%<br>0%<br>Russia CEE CA EN WB MENA Turkey<br><!-- End of picture text --> Source: Authors’ calculations based on Enterprise Survey data.

As described earlier, ESG practices differ by sector. Since the ES sample is representative in a relatively small number of sectors, there is limited room for deeper analysis. Firms in the manufacturing sector tend to have the highest “Corporate ESG Responsibility” composite indicator, while firms in the retail sector tend to have the lowest. Firms in MENA countries have a poor performance across all sectors, with the retail segment - where small companies are more prevalent - showing the worst results. The manufacturing sector in MENA is significantly weaker than manufacturing in most of the other regions in terms of ESG practices.

**Figure 11 - Average quality of Corporate ESG Responsibility, by sector and region** (composite indicator, z-score)

15
**Table I4: Relationship between food security measures and height-for-age z-scores (Uganda): Limited Controls Version**

||(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
|VARIABLES||Heig|ht-for-age z-s|cores||
|1-SSEXR|0.071*<br>(0.041)|||||
|FCS||0.197***<br>(0.038)||||
|DDS|||0.085**<br>(0.041)|||
|PC expenditure||||0.139***<br>(0.041)||
|Food Share|||||0.029<br>(0.038)|
|Rural|-0.599***|-0.544***|-0.599***|-0.555***|-0.638***|
||(0.106)|(0.104)|(0.106)|(0.106)|(0.102)|
|Kampala|0.127|0.069|0.092|0.038|0.178|
||(0.223)|(0.220)|(0.225)|(0.228)|(0.223)|
|Central without Kampala|0.148|0.142|0.114|0.139|0.183|
||(0.119)|(0.116)|(0.122)|(0.118)|(0.117)|
|Eastern|0.208*|0.193*|0.172|0.223**|0.246**|
||(0.117)|(0.113)|(0.123)|(0.112)|(0.113)|
|Northern|0.135|0.245**|0.165|0.233**|0.202*|
||(0.116)|(0.110)|(0.112)|(0.109)|(0.110)|
|Constant|-0.968***|-1.034***|-0.958***|-1.027***|-0.974***|
||(0.121)|(0.121)|(0.121)|(0.122)|(0.122)|
|Observations|2,011|2,010|2,011|2,011|2,011|
|R-squared|0.026|0.038|0.027|0.030|0.025|

Source: Authors’ calculations. Note: Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1 1-SSEXR is the expenditure share of non-starchy staple food in total food expenditure, FCS is the food consumption score, DDS is the household level dietary diversity score, PC expenditure is the per capita expenditure, and Food share is the share of food expenditure in total expenditure.

107
at the local level of the governance of regulatory institutions.

More recently, policy makers in developing countries have pushed further the process of reforms of their infrastructure industries. After a period of implementation of policies of liberalization and privatization of some segments coupled with the creation of regulatory authorities, large efforts have been allocated to improve the efficiency of the working of these authorities. Degree of independence, capacity of human capital, and particularly quality of governance are the three policy items that have mobilized much of these efforts. On the research front, however, both theoretical work on the optimal design of regulatory institutions and empirical work on the measurement of regulatory institutions’ performance suggest that these specific items should not be analyzed independently from more general factors related to the governance of the economy as a whole. The main purpose of this paper is to investigate the relative weight of these factors in regulatory performance by means of an econometric analysis of two data sets on the telecommunications industry in developing and developed countries.

The determinants of regulatory performance have been discussed both in the theoretical and empirical streams of the literature on infrastructure industries regulation. For our purpose, we distinguish two approaches. A first approach, which is conceptual in nature and inspired by political science, argues that when thinking about regulatory performance the relevant game is to be found upstream at the (higher) level of politics (Spiller and Tommasi, 2003). Another more empirical approach emphasizes the impact of regulatory governance on performance (Cubbin and Stern, 2005b). Our general view is that indeed the relationship between political structures and regulatory processes has to be given due attention when assessing regulatory performance. Hence, our study might be viewed as an attempt to merge both of these approaches in order to feed in some empirical elements to the debate on the relationship between political and regulatory institutions that so far has mainly taken place at a conceptual level.

Our empirical strategy consists in implementing a series of econometric tests with a special attention given to variables that capture political account3
**Information campaign** Households were informed of the discounts the month before they took effect in two ways: (1) through a note left on the “Comments” section of the bill, which was handed to each customer upon their monthly in-person payment at a central location in the village, shortly followed by (2) a letter sent by the water utility to each customer’s home.<sup>10</sup> To make the discounts particularly salient just before they were to go into effect, any rebate as a result of a discount was applied retroactively to the prior month’s bill and consumers were informed that henceforth this would be the prevailing rate.

Price salience was confirmed by households inasmuch as 97 percent of them responded within rounding error of the actual price of VND5,300 when asked in the quarterly monitoring survey of December 2015 (at the end of the price linearization phase) what price per cubic meter they expected to be charged the following month. Evidently, households were not only well aware of the price of piped water but of the existence of the on-going linearization scheme as well. Broad awareness of the price flattening is suggested by the fact that even among the 16 percent of households who consumed 10 m<sup>3</sup> or more in December 2015, and who would therefore have paid a higher marginal price absent the linearization scheme, 97 percent still accurately reported within rounding error of the exact price. During this initial phase of the experiment, households were also informed of the imminent subsidy program, although its timing and magnitude were not revealed until the last minute.

# **2.2 Preliminary analysis**

Most of the experimental sample households (70 percent) were connected to piped water in the initial roll-out of An Thinh’s network from September 2012 to February 2013, with the remainder connecting throughout the rest of 2013 (10 percent), 2014 (9 percent), and 2015 (11 percent). Prior to the arrival of piped water, rainwater stored in concrete tanks was the principal source of domestic water supply; for 83 percent of households, internal piping and plumbing fixtures were already in place for conveying rainwater. Appendix Table B.1 shows household water usage patterns at baseline; all but three households report using piped water. More than half of the sample (806 households) report still using some rainwater for cooking and drinking (rainwater is filtered for household use and typically boiled before drinking), and half also report using either rainwater or groundwater for shower and bathroom needs. In short,

> 10Nonpayment or delinquency on water bills is virtually non-existent in our setting.

8
unemployment rate in (12) was estimated at 13.32 percent using data for October 1998. The impact of agro-manufacturing trade liberalization in developed countries can be estimated as The last column of Table 3 shows that a 10 percent increase in the price of agro-manufactured exports would cause the unemployment rate to decline by 1.23 percentage points, i.e., from approximately 13.32 to 12.09 percent. This is a substantial change: higher export prices would bring the unemployment rate down by roughly 10 percent.

To relate this type of trade reform with poverty, I look at the employment-unemployment effects separately for the poor and the non-poor. In the second and third rows of Table 3, I report that the impacts tend to be rather similar for these two groups. For instance, the probability of becoming employed increases by 1.45 percentage points for the poor and by 1.34 percentage points for the non-poor. Interestingly, the probability of being unemployed declines by more for the non-poor ( _−_ 0 _._ 78 percentage points) than for the poor ( _−_ 0 _._ 74 points), but the change in the probability of participating in the labor market increases more for the poor (0.67) than for the non-poor (0.60). This is because the majority of inactive individuals before the price change is actually poor. Notice, however, that all these differences are hardly significant (from a statistical viewpoint). The same pattern can be discerned across quintiles of household per equivalent adult income. The changes in the probability of being employed are relatively similar across quintiles: from 1.46 percent in the first quintile, to 1.17 percent 28
18 (their) circumstances, which are {ethnicity, father in agriculture, father’s education, mother’s education, birth region}. Surely the inclusion of parental education in the Ferreira-Gignoux data set increases the role of circumstances in generating inequality.

Figure 4a presents the distribution functions of disposable income for the Brazilian types (white, male household head, urban), (white, female household head, urban), (white, male household head, rural) in order of stochastic dominance (using the Higgens-Pereira data set). Thus, it appears that one has better opportunities if one is raised by a woman in the city than by a man in the countryside. Figure 4b presents the analogous three distribution functions for the mixed race. The order of stochastic dominance is the same as in figure 4a. Figure 4c places these two plots together: we see that even the _most disadvantaged_ white type first-order-stochastic-dominates the _most advantaged_ mixed type.

It turns out that the three black types also have distribution functions ordered in the same way. Figure 5 presents the distribution functions of the black types (in violet) superimposed upon figure 4c. We observe that the first two black types ((male household head, urban) and (female household head, urban)) have distribution functions that are virtually coincident with the analogous mixed types, and the distribution function of (black, male household head, rural) appears to FOSD the comparable ‘mixed’ type. Indeed, the distribution function of the (black, male household head, urban) type is virtually invisible in figure 5, as it coincides so closely with that of the (mixed, male household head, urban) type. The conclusion appears to be that there is racial discrimination in Brazil which favors whites over non-whites, but there is no special
the North American Free Trade Agreement (NAFTA) led to a rapid growth in export industries-Mexico had US$21.5 billion growth in exports from 1994 to 1998, compared to just US$6 billion in export growth from 1991 to 1994 (World Bank 1999).

According to the latest available national employment survey (ENE99), the economically active population (EAP), defined as the sum of the employed population and the open unemployed population, numbered nearly 40 million people. The average net participation rate was nearly 56 percent. From 1995 to 1999, the open unemployment rate decreased from 4.7 percent to 1.7 percent.<sup>4</sup> Mexico's labor force grew at an average rate of 2.8 percent per year from 1995 to 1999. This means that nearly 1,113,000 new entrants were added to the labor force every year.

Women's labor force participation, while still low compared to the level in developed economies, rose significantly in the 1990s. Data from the Organisation for Economic Cooperation and Development (OECD) shows that the rate for women 25-54 years old increased from 37 percent in 1990 to 44 percent in 1998 (OECD 1999). The other important feature of the late 1990s, according to the International Labour Organisation (ILO) data, is that labor force growth and declining open unemployment were accompanied generally by rising real salaries and wages in manufacturing. This was after a more than 30 percent decrease in real manufacturing wages from 1982 tol988.

> 4 Mexican wages are likely to increase in real terms for the third consecutive year in 2000, by three to five points above inflation. The improvement fits with the pattem of booming economic growth in Mexico in 2001, coupled with a steady curbing of inflation. The latest government figures show that the economy grew by 7.5 percent during the first seven months of the year 2000, compared with 3.7 percent in the whole of 1999. Twelve-month accumulated inflation was down to 9.10 percent at the end of August, compared with 12.3 percent at the start of the year. Nevertheless, experts agree that, with inflation under control, wage increases during 2001 must be backed by increases in productivity in order to prevent a renewed increase in inflation.

8
<!-- Start of picture text --> ee «<br>1.5 “<br>at,<br>*<br>10<br>+<br>0.5 .<br>0.0<br>1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020<br>= Agriculture == Manufacturing = Services<br><!-- End of picture text --> <!-- Start of picture text --> 0<br>10<br>. .<br>*<br>-20<br>.<br>ot<br>-30<br>* +,<br>*<br>1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020<br>= Agriculture = Manufacturing = Services<br><!-- End of picture text -->
(1999), Rodrik (2006)), and if the output cost of a financial crisis is about 10 percent of GDP, as found by Hutchison and Noy (2006). Similar results have been obtained using more elaborate models (Garcia and Soto (2004); Jeanne and Ranciere (2006)).

One challenge to the Guidotti-Greenspan rule came from the concern that it focused on exposure to external volatility in the form of a sudden stop in capital inflows. Yet, policy makers may also accumulate reserves as a buffer against internal volatility. Domestic instability may trigger internal conflicts, leading to ―sudden capital flight.‖ In these circumstances, the private sector would opt to swap domestic currency assets with assets denominated in foreign currency (Calvo (2006)). Obstfeld, Shambaugh and Taylor (2010) found that the liquid liabilities of the banking system as measured by M2 provide a good proxy for the domestic exposure to such liquidation shocks. A higher ratio of international reserves to M2 would provide a thicker cushion, thereby reducing the adverse effects of sudden capital flight on the real exchange, and possibly even reducing the probability of a sudden capital flight crisis in the first place (to the extent that such a crisis has a self-fulfilling element).

Calvo‘s ―sudden capital flight‖ concerns were vividly illustrated by the Argentine financial meltdown of the early 2000s. The hope that backing the monetary base by international reserves would prevent exchange rate instability was dashed. A lesson of the Argentine crisis is that currency boards and fixed exchange rate arrangements should be supported with stringent prudential supervision, and the dynamic management of reserves. Reserves should be well above the monetary base, reflecting the entire balance sheet of the economy. The experience of Hong Kong SAR, China, supports this logic, suggesting that enduring fixed exchange rate regimes are feasible provided there is constant investment in credibility, including possibly by a decrease in the discretionary element of policies (see Genberg and Hui (2011)). A hefty international reserve position, well above the monetary base, and a large sovereign wealth fund, would help.

The second challenge came from an analysis of post-1998 trends in hoarding reserves, especially in East Asia. The greater flexibility of the exchange rates should have worked in the direction of reducing reserve hoarding, but the opposite was clearly happening. While the Guidotti-Greenspan rule focused on the ratio of reserves to short-term debt, Kim et al. (2005) looked at a more flexible rule based on the behavior of different types of capital flows. An application to selected Asian countries led them to conclude that the countries affected by the East Asian crisis held excessive reserves by 2003— the affected countries had already built up more than adequate reserve levels to handle a repeat of the actual capital outflows that occurred during the 1997–98 crises scaled up to 2003 values.

13
on influential committees such as the House Agriculture committee. Therefore, the top-20 Senate Ag PAC lists in Figures 7.1-7.5 contain names of Senators who are from states with influential agricultural constituencies but may or may not be members of the Agriculture, Nutrition and Forestry committee. A case in point is the absence of the chair of this committee in 1991-92 (Sen. Leahy, VT, ranked 33<sup>rd</sup> among Ag PAC recipients), but the presence of Senators from Missouri which was the 12<sup>th</sup> ranked state in 1992 according to market value of agricultural products sold (U.S. Department of Census, 1997), Wisconsin, ranked 8<sup>th</sup> , Oklahoma ranked 17<sup>th</sup> , Indiana ranked 11<sup>th</sup> , Arkansas ranked 13<sup>th</sup> , Pennsylvania ranked 18<sup>th</sup> , and Georgia ranked 19<sup>th</sup> . Senators from other states appearing in Figure 7.1 but not ranked highly according to total value of agricultural products sold were nevertheless ranked highly in output of specialized products. Thus, Senators were sought by: potato interests in Idaho, tobacco and livestock interests in Kentucky, peanut and poultry interests in Alabama, tobacco interests in South Carolina.

Nor does it appear that there was a strong desire among senators to become members of agriculture committees. Representing states with strong agriculture interests was sufficient to guarantee them Ag PAC money. This was especially true among the top-20 Ag PAC Senate recipients in the 1993-94 (Figure 7.2), 1997-98(Figure 7.4) and 1999-00 (Figure 7.5) election cycles. Figure 7.2 for example indicates that agriculturally rich states represented by strong Ag PACs (Texas, Montana, Washington, California) gave to their Senate candidates regardless of committee membership. The same was true of the 1997-98 and 1999-00 election cycles. A reasonable conclusion is that there does not appear to be simultaneity between the amount of PAC spending and committee membership. Evidence of that simultaneity appears to be much stronger for House candidates.

36
37 Table 4: RER Elasticitv with Resvect to Fiscal Variabl.e

|||(P|ercentage C|hange in RER|)|||
|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|10% Rise in:|RPT|RPX|RPM|RPTJ|RPXl|RPM.1|<br>RERT|
|Capital<br>Exp./Total<br>Govt. Exp.|-3.81|-3.81|-3.76|-4.79|-4.71A|<br>4.74|n.s|
|Total Govt.<br>Exp/GDP|-5.55|-5.57|-5.63|-9.64|-9.71|-9.71|-11.54|

Source: Computed using mean values of fiscal variables and coefficients from TabLe 3.