rafmacalaba/datause-encoder-data huggingface dataset:
# **5.2.2 FDI**

Next, I explore the effects of unreliable electricity provision on the entry of foreign firms via FDI. In many developing and emerging countries, FDI is a potent source of firm entry as foreign investors enter these markets to harness the natural and human capital, and establish businesses in these economies. These new firms ultimately generate jobs for local people (Toews and V ́ezina, 2021). For instance, Toews and V ́ezina (2021), using data on Mozambique estimates to estimate the FDI-local job multiplier finds that each new FDI-job creates an additional 4.4 jobs of which 2.1 are formal jobs. In other words, aside the direct jobs creation associated with FDI’s (eg., employment of factory workers), FDI’s generates indirect jobs resulting from sectoral linkages.<sup>54</sup> Thus, FDI is a key channel for job creation in many developing countries, hence, factors that constrain FDI flows could have negative implications on employment.

The economic effects (including employment) associated with FDIs have made the attraction of FDI a key development strategy of emerging economies. However, the quality of infrastructure provision such as electricity plays an important role in the flow (direction) of FDI to developing economies. Cost of doing business is an important driver of FDI flows as it influence the returns on investment to investors. Meanwhile, the reliability of electricity provision is a significant determinant of the cost of doing business. For instance, during blackouts some firms rely on in-house electricity generation which are expensive relative to grid supply, while others curtail production. These options invariably have negative effects on firms’ profitability. In addition, persistent reliability issues in the electricity sector can generate adverse macroeconomic shocks in the economy thereby affecting investor confidence.

In section, I ask: to what extent does unreliable provision of electricity affect FDI flows? To address this question, I exploit the ”Dumsor” power crisis in Ghana as a natural exper54For instance, FDI into manufacturing, may generate increased demand for intermediate inputs within the value chain, which ultimately creates jobs.

40
to implement and monitor the diary-based survey, and refusal rates are likely to be high among affluent households who find the diary reporting method a costly use of their time. Second, much of the difference between levels and trends from the NBS and RCRE surveys can be explained by differences in the valuation of home-produced grain and in the treatment of taxes and fees.

# 2.3 Trends in Migration, Consumption Growth and Poverty

One of the benefits of the accompanying village survey are questions asked annually of village leaders about the number of registered village residents working and living outside the village. In our analysis, we consider all registered village residents who work outside the home county to be migrants.<sup>13</sup> Both the tremendous increase in migration from 1987 onward and heterogeneity across villages are evident in Figure 1. In 1987 an average of 3 percent of working age laborers in RCRE villages worked outside of their home counties, and this share rose steadily to 23 percent by 2003. Moreover, we observe considerable variability in the share of working age laborers working as migrants. Whereas only a small share of legal residents are employed as migrants in some villages by 2003, more than 50 percent of working age adults are employed outside their home county from other villages.

The relationship between migration and consumption is of central concern for our analysis. The linear fit of the relationship between annual changes in share of the village workforce employed as migrants (village migrant share) and growth in village average consumption in the RCRE data suggest a positive relationship (Figure 2). The lowess fit, however, suggests the presence of nonlinearities, particularly around zero. The prospect that out-migration may be driven by negative shocks or return migration by positive shocks, which are correlated with movements in consumption, should raise concern that migration and consumption are endogeneous.

Even if consumption grows with an increase in the number of residents earning incomes from migrant employment, it is of particular policy interest to understand which residents within villages are experiencing increases in consumption. Changes in the village poverty headcount are negatively associated with the change in the number of out-migrants, suggesting that poverty declines with increased out-migration (Figure 3). Nonlinearities in the bivariate relationship are again evident in the lowess plot of the relationship. Whether obvious nonlinearities are related to the simultaneity of shocks and increases in out-migration and poverty for some villages or to the simple fact that

> 13 From follow up interviews with village leaders, it is apparent that registered residents living outside the county are unlikely to be commuters and generally live and work outside the village for more than six months of the year.

6
inefficiency of the new trade defense instruments. Both aspects —crucial for a new modernizing process— were beginning to be strongly and dangerously questioned all over the country.

One of the ways in which the Mexican government responded was by filing an _ex officio_ antidumping investigation package against products of Chinese origin, for which high antidumping duties were applied; since the initiation of the investigation was published in conformity with the Law Regulating Article 131, i.e. two months before the publication of the new Foreign Trade Act. Provisional duties were applied to around 3,000 tariff items.

**Table 7 - The “China Package” and Other Cases against Chinese Products during 1993**

||||**Date of**|**Date of final**|**Duty applied upon**||
|---|---|---|---|---|---|---|
|**#**|**Product**|**Country**|**initiation **|**determination **|<br> <br>**initiation**|**Final duty applied**|
|1|Toys*|China|14-Apr-93|25-Nov-94|351%|351%|
|2|Shoes*|China|15-Apr-93|30-Dec-03|1,105%|1,105%|
|3|Tools*|China|15-Apr-93|11-Nov-94|312%|312%|
|4|Clothing*|China|15-Apr-93|18-Oct-94|533%|533%|
|5|Chemicals*|China|15-Apr-93|18-Oct-94|673%|209%|
|6|Textiles*|China|15-Apr-93|18-Oct-94|501%|501%|
|7|Electrical machines and<br>equipment*|China|15-Apr-93|18-Nov-94|129%|129%|
|8|Bicycles|China|15-Apr-93|22-Sep-94|594%|279%|
|9|Pencils|China|09-Aug-93|18-Oct-94|451%|451%|
|10|Valves|China|01-Nov-93|18-Oct-94|0|105%|
|11|Pencil sharpeners|China|19-Nov-93|18-Oct-94|0|145%|
|12|Baggage and bags|China|29-Nov-93|25-Nov-94|0|0|

* Cases corresponding to the China Package. Source: Based on data from World Trade Atlas and several DOF.

The decision to initiate investigations and impose high antidumping duties against Chinese products was important from the political perspective. However, its impact from the commercial point of view had been carefully considered. Mexico did not breach any international trade agreement, since these investigations involved products from a non-WTO Member. Additionally, most antidumping duties were applied to consumer goods, thus avoiding any impact on Mexican exports’ competitiveness.

Table 8 below illustrates —through the multi-country/multi-product steel cases filed in the same year the China Package was published— some aspects of the ambivalent and apparently 26
Table 4: Effect of Family Planning Access on Number of Children Ever Born for Women Without Schooling

||Children|Ever Born||
|---|---|---|---|
||OLS|IV Model<br>Plac|of Predicted<br>ement<sup>a</sup>|
||Model I<br>Model II|Model III|Model IV|
|Family planning|_−_0_._687<sup>_∗∗∗_</sup>|_−_0_._892<sup>_∗∗∗_</sup>||
||(0_._215)|(0_._323)||
|Family planning_×_age 15-19|_−_0_._656<sup>_∗∗_</sup>||_−_1_._052<sup>_∗∗_</sup>|
||(0_._288)||(0_._412)|
|Family planning_×_age 20-24|_−_0_._219||_−_0_._281|
||(0_._254)||(0_._465)|
|Family planning_×_age 25-29|_−_0_._302||_−_0_._899<sup>_∗∗_</sup>|
||(0_._236)||(0_._448)|
|Family planning_×_age 30-34|_−_0_._919<sup>_∗∗_</sup>||_−_0_._925|
||(0_._395)||(0_._590)|
|Family planning_×_age 35-39|_−_0_._928<sup>_∗∗∗_</sup>||_−_0_._700<sup>_∗_</sup>|
||(0_._339)||(0_._418)|
|Family planning_×_age 40-45|_−_0_._932<sup>_∗_</sup>||_−_1_._269<sup>_∗∗_</sup>|
||(0_._487)||(0_._604)|

**Notes.** * sign. at 10%; ** sign. at 5%; *** sign. at 1%. Robust standard errors clustered at community level in parentheses. Family planning indicates whether there was family planning available within 40 km in 1990. Additional variables not shown are region dummies, ethnic group dummies, five year age group dummies, dummies for religion, area of wereda, rainfall and rainfall squared of wereda, dummy for urban area, dummy for market in area, and dummies for road access all year and road access only during dry season. Number of observations for all models is 1326. Results for including other explanatory variables are in Table A-1. a Weighted IV estimation using Stata’s svy command with family planning access treated as endogenous.

ning reduces fertility more among younger and older women. In particular, the OLS results show that the reduction in number of children is 0.6 for the youngest age group, aged 15-19, smaller and not statistically significant for women between 20 to 29 and then large and statistically significant at just below 1 for women aged 30 to 45. Except for women aged 35 to 39, the IV effects are larger than the OLS effects. For women less than 20 years old taking account of program placement almost doubles the effect of family planning on number of children; the IV result indicates that family planning access decreases the number of children born by 1 for the youngest women. In other words, young women substantially delay their child bearing when they have access to family planning.

Because few women give birth after age 45, the estimated effect for the oldest age group is an indicator of the impact of family planning access over most of a woman’s reproductive years on completed fertility. For the oldest age group, women aged 40 to 45, the IV results are also larger than the OLS results. According to the IV results access to family planning decreases completed fertility by 1.3 children among 40-45 old women without education. More precisely, women who received access to family planning later in their 15
**<u>Table 9. Performance Comparisons between SOEs and Privatized Firms</u>**

|Variables|N<br>d|Mean<br>Before<br>(Median)|Mean<br>After<br>(Median)|Mean<br>Change<br>(Median)|Z-Statistic for Difference in Means<br>(After-Before)<br>(p-value)|
|---|---|---|---|---|---|
|**Net Profit Level** <br>**a**<br>Privatized<br>SOE<br>|39<br>41|0.79<br>(0.59)<br>1.64<br>(1.25)|1.59<br>(1.14)<br>1.00<br>(0.95)|0.80<br>(0.55)<br>-0.64<br>(-0.30)|3.44***<br>(0.001)<br>-1.28<br>(0.20)|
|**Employment**<br>**b**<br>Privatized<br>SOE|41<br>41|4660<br>(1862)<br>2638<br>(1594)|4784<br>(1914)<br>2635<br>(1426)|124<br>(116)<br>-3<br>(-168)|2.48***<br>(0.01)<br>-1.114<br>(0.26)|
|**Sales Efficiency**<br>**c**<br>Privatized<br>SOE|41<br>41|0.71<br>(0.68)<br>1.35<br>(1.23)|0.84<br>(0.73)<br>1.06<br>(1.01)|0.13<br>(0.06)<br>-0.29<br>(-0.22)|3.04***<br>(0.00)<br>-2.86***<br>(0.00)|

Notes: The mean (median) values before and after year zero (1996, the year when the 41 firms were privatized) are calculated separately for each group. The before calculation uses a two-year average (199495) and after a three-year average (1997-99). The Wilcoxon signed rank test (z-statistic) is the significance of the mean change. The ‘mean before’ and ‘mean after’ values for net profit level and sales efficiency are normalized using the year zero (1996 = 1.00) value. **a** Net income after taxes; **b** Total No. of employees; **c** Sales/total employment; d No. of usable observations. ******* Significant at the 0.01 level. Source: Wei, Zuobao, et al. (2003).

However, though very promising, due to various constraints and limitations, the full potential of the private sector is far from being released. Instead, the private firms have to remain under a veil of informality, and have a limited ability to evolve beyond the first, informal stages of life and tend to become “stuck” in a framework of legal, financial, governance, and market structures because of their informal status.

**Figure 4 Private Sector Development in China**

<!-- Start of picture text --> 3000<br>2500<br>No. of Enterprises<br>2000 (1,000)<br>Employment<br>1500 (10,000)<br>1000 Sales (RMB,<br>billion)<br>500<br>0<br>1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000<br><!-- End of picture text --> _Source_ : International Finance Corporation Beijing office, and Helmut Schonleber, “China’s Private Economy,” presentation for the DIHT-ACFIC Partnership Project, 2001.

16
Figure 1 suggests that the first question a researcher can ask is whether poverty estimates are to be produced on a monetary (or money-metric) basis. If the answer to this question is no, the relevant imputation method is to construct an asset (wealth) index, and this method is discussed in more detail in Section II. If the answer is yes, the next useful question is whether the desired poverty estimate is nationally representative. If the answer to this question is no, proxy means testing is likely the relevant method (Section III). A yes to this question leads to the third question of whether the poverty estimate will be used for dynamics analysis, which involves an examination of household movements into or out of poverty based on synthetic panel data (Section VI).

A no to this question leads to the fourth question of whether the poverty estimate will be disaggregated below the national level. If yes, techniques commonly known as “poverty mapping” (or small-area estimation techniques) are most relevant. Another name for these techniques is survey-to-census imputation, where the imputation model is first built from a survey and subsequently applied to a census, since the latter offers reliable disaggregate data (Section V). If no, survey-to-survey imputation methods are likely most appropriate. The final question is whether the imputation will involve surveys of the same design. Within-survey imputation (Section IV.1) and across-survey imputation (Section IV.2) should be respectively employed if imputation is done on surveys of the same design or of a different design.

A related but different classification is offered in Dang _et al._ (2017a), where a poverty imputation situation is classified according to the degree of missing consumption data. We present a slightly modified version of this classification in Table 1, which offers three categories in a roughly decreasing order of the severity of missing consumption data: completely missing (Category A), partially missing (Category B), and available cross-sectional data but missing panel data (Category C). In other words, while Figure 1 focuses on the functional or practical aspects of 5
# 1. <u>INTRODUCTION</u>

Trinidad and Tobago (T&T) is a high-income country<sup>2</sup> , rich in natural resources, with a welldeveloped globally competitive oil and gas industries. The country can be characterized as a dual economy. Its energy sector is very productive, export-oriented, and exhibits high rates of returns to investment. However, while the energy sector represented 65.8% of exports and 44.0% of gross domestic product (GDP), it only employed 3.1% of the labor force over the last decade<sup>3</sup> . On the other hand, the non-energy sector is underdeveloped, attracts little investment and, for a significant part, depends on government subsidies and transfers. Between 1994 and 2008, the country’s output grew at an impressive average rate of 7.1%<sup>4</sup> . Yet, most of this growth can be attributed to the performance of the oil and gas sectors supported by high energy prices. Over the last decade, average annual GDP growth in the petroleum sector averaged 9.7%. The non-energy sector on the other hand exhibited much slower growth rates with a decade mean of 3.6%<sup>5</sup> . T&T’s economy has historically been quite volatile and particularly vulnerable to commodity price shocks (see Figures 1.1 and 1.2).

At current rates of resource extraction, it is estimated that by 2025-2030 gas and oil fields will be fully depleted. This brings into sharp focus the issue of diversification. While successive governments have developed growth strategies to balance economic activity and raise activity in the non-energy sector, there is little evidence of success over the last 25 years. This highlights the issue of identifying and alleviating the binding constraints to T&T’s economic diversification. How can the country achieve a sustainable and balanced growth? What is there to be learned from the experience of other resource rich and commodity exporter countries? What are the drivers and obstacles of economic diversification in T&T?

This work is an attempt to find solutions to the various questions highlighted in the preceding paragraph through the use of various econometric estimations and qualitative analysis. This study exploits a large panel data set covering 183 countries over the period 1980-2010 to analyze historical global diversification patterns with a particular focus on T&T. Unlike similar studies, the results in this paper are strengthened through the use of the general method of moment econometric methodology to infer causality. The paper finds that openness to FDI, access to finance, real exchange rate and terms of trade shocks are fundamental determinants of economic diversification. Therefore, greater openness to FDI and improving the business climate emerged as crucial policies to extend the structure of a country’s economy.

> 2 GNI per capita was US$14,710 in 2012 (World Development Indicators).

> 3 Central Bank data and WB staff estimates.

> 4 WEO data and WB staff estimates.

> 5 Central Bank data and WB staff estimates.

3
# **Table 3 (OLS Models, Continued)**

|**Panel C: Returns to Years of Schooling -- Piecewise Line**|**ar Spline**||||
|---|---|---|---|---|
|Model<br>Variable|1<br>ln(wage)|2<br>ln(wage)|3<br>ln(wage)|4<br>ln(wage)|
|Years of Schooling for Years>12|0.135|0.135|0.129|0.119|
||(0.007)|(0.007)|(0.007)|(0.007)|
|Years of Schooling for Years<=12|0.063|0.062|0.054|0.053|
||0.007|0.008|0.007|0.008|
|Other Included Regressors|||||
|City and Birth Year Dummy Variables|Yes|No|No|No|
|Three Year Birth Cohort x City Dummy Variables|No|Yes|Yes|Yes|
|Height, Female and Height x Female|No|No|Yes|Yes|
|Parent Education Variables and Number of Siblings|No|No|Yes|Yes|
|School Quality and Parent Occupation Variables|No|No|No|Yes|
|N|3613|3613|3610|3610|
|R-Squared|0.302|0.316|0.329|0.341|
|Notes:|||||

All models include measures of age and age-squared (age is measured from month of birth to November 2001), height (in centimeters), an indicator for gender (female=1), and height **x** gender. Robust standard errors are cluster corrected at the city-birth cohort level.

36
<!-- Start of picture text --> Figure 2a: Revenue, % of GDP, average (non-weighted)<br>45<br>. JN<br>30a<br>iii<br>20<br>15<br>2000 2001 2002 2003 2004 #2005 i#2006 2007 +2008 #2009 2010<br>——ECA =——Oil& Gas Exporters -—=EU10,Cro, Tur —LICs&LMICs=m<br><!-- End of picture text --> <!-- Start of picture text --> Figure 2b: Revenue, % of GDP, average (weighted by GDP)<br>50<br>A5 /\<br>.<br>»_L<br>15<br>2000 2001 2002 2003 2004 2005 #2006 2007 2008 =$.2009 2010<br>——ECA =——Oil&Gas Exporters —==EU10,Cro, Tur =LICs= & LMICs<br><!-- End of picture text -->
Caprio, and Levine (2006). We take that politics and finance are far from independent as a given, and set out to document a particular mechanism –that of former politicians sitting in banks’ boards of directors- through which this may be working in practice.<sup>4</sup> A recent strand of the literature has documented that good things do happen to firms that are politically connected.<sup>5</sup> In a paper very close to ours, Faccio (2006) shows that the overlap between controlling shareholders and (current) government officials is quite widespread across countries, and seems to have a positive impact in the connected firms’ value via regulation. We take this lead –especially in the way the phenomenon is measured- and complement the line of research by focusing on banks and by providing further evidence on what happens to the other groups likely to be involved in this game: politicians appear to be also benefiting, while the public seems to suffer from poorly developed financial system. We also allow these connections to be based not only on current links but also on interactions at different moments in time.

The rest of the paper is structured as follows. Section 2 describes the data and the matching procedure used to measure the prevalence of the banker-politician phenomenon. Section 3 presents our results on what kind of politicians and banks are more likely to be related this way, and where this happens more often. Section 4 concludes.

# **2. Measuring the Prevalence of Banker-Politicians**

The basic sources of data for politician names were the _Economist Inteligence Unit Country Reports_ , which we revised twice a year for each country between 1996 and 2005. From this we obtained a total of 72,769 names of cabinet members and central bank governors. These names were complemented by a smaller set of 593 names of financial sector supervisors obtained from the 2000, 2002, 2003, and 2004 issues of _How Countries Supervise their Banks, Insurers and Securities Markets_ . These two sets together provide extensive coverage for cabinet members and financial sector supervisors in about 150 countries.

The names of banks’ board members come from _Bankscope,_ which has data on both listed and unlisted banks in about 150 countries at one moment in time (generally December 2005). A total of 109,645 board member names were collected. Although this is the most comprehensive source of data on bank information around the world, only a fraction of banks in 4 The mechanism has been vividly documented in recent historical country case studies such as Maurer and Gomberg (2005), Maurer (2002), and Razo (2009).

> 5 See, for instance, Faccio (2006), Fisman (2001), Faccio, Masulis, and McConnell (2005), and Khwaja and Mian (2005).

4