rafmacalaba/datause-encoder-data huggingface dataset:
# **Good Enough for Outstanding Growth: The Experience of Bangladesh in Comparative Perspective**<sup>*****</sup>

**_Robert C. M. Beyer_** _World Bank_ <u>rcmbeyer@worldbank.org</u>

**_Konstantin M. Wacker_** _University of Groningen_ <u>k.m.wacker@rug.nl</u>

**<u>Keywords</u>** : growth, economic development, institutions, reform, Bangladesh

**<u>JEL Classifications</u>** : O11, O47, O53

> * Corresponding author: Konstantin M. Wacker (k.m.wacker@rug.nl). The authors would like to thank Zahid Hussain, Mustapha Nabli, Hoon Soh, Yutaka Yoichiro, Bernard Haven, Nazmus Khan, Nora C. Dihel, Lei Lei Song, and Weh-Sol Moon, as well as participants of the Asian Economic Development Conference 2022 and workshops at the World Bank and SANEM for helpful comments (including on earlier versions of this paper). Eline Koopman provided excellent research assistance.
**Appendix B. List of survey waves in the WBES’ standardized data set for the period 2006-2022**

**Table B.1. List of survey waves.**

|**Country**|**Freq.**|**Percent**|**Cu**|**m.**|**Country**<br>**Fr**|**eq.**<br>**Per**|**cent**|**Cum.**|
|---|---|---|---|---|---|---|---|---|
|Angola 2006|212|1.63||1.63|Ethiopia 2011|258|1.98|19.29|
|Angola 2010|71|0.55||2.17|Ethiopia 2015|335|2.57|21.86|
|Benin 2009|71|0.55||2.72|Gambia, The 2006|32|0.25|22.1|
|Benin 2016|63|0.48||3.2|Gambia, The 2018|72|0.55|22.66|
|Botswana 2006|114|0.88||4.08|Ghana 2007|284|2.18|24.84|
|Botswana 2010|85|0.65||4.73|Ghana 2013|371|2.85|27.69|
|Burkina Faso 2009|82|0.63||5.36|Guinea 2006|130|1|28.68|
|Burundi 2006|98|0.75||6.11|Guinea 2016|24|0.18|28.87|
|Burundi 2014|59|0.45||6.56|Kenya 2007|390|2.99|31.86|
|Cameroon 2009|97|0.74||7.31|Kenya 2013|383|2.94|34.8|
|Cameroon 2016|97|0.74||8.05|Kenya 2018|451|3.46|38.26|
|Cabo Verde 2009|56|0.43||8.48|Lesotho 2016|74|0.57|38.83|
|Central African Republic 2011|36|0.28||8.76|Liberia 2017|75|0.58|39.41|
|Chad 2009|60|0.46||9.22|Madagascar 2009|199|1.53|40.94|
|Chad 2018|73|0.56||9.78|Madagascar 2013|251|1.93|42.86|
|Côte d'Ivoire 2009|170|1.31||11.09|Mali 2007|301|2.31|45.17|
|Côte d'Ivoire 2016|103|0.79||11.88|Mali 2010|154|1.18|46.36|
|Congo, Dem. Rep. 2006|149|1.14||13.02|Mali 2016|92|0.71|47.06|
|Congo, Dem. Rep. 2010|123|0.94||13.97|Mauritania 2006|80|0.61|47.68|
|Congo, Dem. Rep. 2013|234|1.80||15.76|Mauritania 2014|28|0.21|47.89|
|Djibouti 2013|60|0.46||16.22|Mauritius 2009|203|1.56|49.45|
|Eswatini 2006|68|0.52||16.74|Mozambique 2007|340|2.61|52.06|
|Eswatini 2016|73|0.56||17.31|Mozambique 2018|285|2.19|54.25|

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<!-- Start of picture text --> Year trends for employment<br>1<br>c)<br>§<br>= 8<br>S= 7<br>GB 6<br>8s<br>2<br>FaSs 4<br>-°<br>& 5<br>Es<br>‘4 °<br>O-- - - - - 5 -<br>1990 1994 1998 2002 2006 2010 2014 2018<br>Survey years<br>-® Afghanistan. -@®- Bangladesh -® India.<br>-* Maldives —* Nepal -* Pakistan<br><!-- End of picture text --> <!-- Start of picture text --> GDP per capita (constant prices)<br>400<br>350<br>x, 300<br>5 250<br>Vv<br>£& 200<br>cg 150<br>g<br>100 a<br>50<br>0<br>1990 1994 1998 2002 2006 2010 2014 2018<br>Year<br>—— Afghanistan; ——Bangladesh —India.<br>— Maldives —Nepal — Pakistan<br><!-- End of picture text --> <!-- Start of picture text --> Total fertility rate (per woman)<br>8<br>7<br>c2 6<br>ne)<br>Fa<br>05<br>“4<br>§3<br>2<br>2<br>1<br>1990 1994 1998 2002 2006 2010 2014 2018<br>Year<br>—— AFG — BoD — IND<br>——MDV —NPL —— PAK<br><!-- End of picture text --> <!-- Start of picture text --> Year trends for years of education<br>10<br>9<br>J<br>Ps<br>Oo 74<br>2<br>3 6<br>2<br>g 3<br>= 2<br>14 bs<br>0<br>1990 1994 1998 2002 2006 2010 2014 2018<br>Survey years<br>—® Afghanistan -®- Bangladesh -@ India<br>—® Maldives —® Nepal —® Pakistan<br><!-- End of picture text -->
To illustrate the quantitative implications of the model, we conduct a calibration exercise with counterfactual simulations. In our model, the Coasian structural parameters determine the gross-output-to-value added ratio, a fact that facilitates calibration. We shock international trade costs and find numerical evidence that is consistent with our theoretical results. We find that shocks to Chinese productivity and to the coordination cost parameter in China to highlight different implications for welfare, spillover to other countries and specialization along production chains. In order to better tie the model to available data, we develop an extension of the calibrated model with an explicit representation of assembly activities to better formalize the participation of China in international production chains.

# **References**

- **Antr`as, Pol and Davin Chor** , “Organizing the global value chain,” _Econometrica_ , 2013, _81_ (6), 2127–2204.

- **, , Thibault Fally, and Russell Hillberry** , “Measuring the Upstreamness of Production and Trade Flows,” _American Economic Review Papers and Proceedings_ , 2012, _102_ (3), 412– 416.

- **, Teresa C Fort, and Felix Tintelnot** , “The Margins of Global Sourcing: Theory and Evidence from US Firms,” _Working paper_ , 2014.

- **Arkolakis, Costas, Arnaud Costinot, and Andres Rodriguez-Clare** , “New Trade Models, Same Old Gains?,” _American Economic Review_ , 2012, _102_ (1), 94–130.

- **Baldwin, Richard** , “Global supply chains: Why they emerged, why they matter, and where they are going,” _C.E.P.R. Discussion Papers_ , August 2012, _9103._

- **and Anthony Venables** , “Relocating the Value Chain: Offshoring and Agglomeration in

- the Global Economy,” _NBER Working Papers_ , 2010, _1661._

- **and Javier Lopez-Gonzalez** , “Supply-chain Trade: A portrait of global patterns and

- several testable hypotheses,” _Working Paper_ , December 2012, pp. 1–57.

- **Baldwin, Richard E.** , “Managing The Noodle Bowl: The Fragility Of East Asian Regionalism,” _The Singapore Economic Review (SER)_ , 2008, _53_ (03), 449–478.

- **Bernard, Andrew B, Andreas Moxnes, and Karen Helene Ulltveit-Moe** , “Two-Sided Heterogeneity and Trade,” _NBER Working Paper no. 20136_ , 2014.

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<!-- Start of picture text --> Job Creation<br>Total Economy<br>020.<br>015<br>0.10<br>0.05<br>0.00<br>oPRR> FF z EREz<e:SEE zGB<br>GEE «Tota! )§= Continuers §=©ER Entrants<br><!-- End of picture text --> <!-- Start of picture text --> Job Creation<br>Manufacturing<br>020.<br>0.15<br>0.10<br>0.05<br>wReSsSeRgteERSEESRRESRSETOESSSESE E GS<br>GEE «Tota! )§= Continuers §=©EE Entrants<br><!-- End of picture text --> <!-- Start of picture text --> Job Destruction<br>Total Economy<br>0.20:<br>0.15<br>0.10<br>0.05:<br>0.00<br>o$eREER> - z Zz<eEESTE Sz 8<br>GE sTotel «= Continuers «= Exiters<br><!-- End of picture text --> <!-- Start of picture text --> Job Destruction<br>Manufacturing<br>0.20:<br>0.15<br>0.10<br>0.05:<br>—SESeSs SR eRtERSSESRREESRSE TH E IRG S<br>GR sTotel «= Continuers «= Exiters<br><!-- End of picture text -->
effects of marginal tax cuts cast doubt on the potential for a double dividend (Bovenberg and de Mooij 1994; Parry 1995; Bovenberg and Goulder 1996; Koskela, Schon, and Sinn 1998). Later, Williams (1999, 2002) and Parry and Bento (2000, 2001) described special situations that might lead to a double dividend. Most recently, Bento and Jacobsen (2007) use a conceptual and numeric model to show that, when rents related to the use exhaustible resources are not fully taxed, net welfare gains constituting a double dividend can be generated when environmental taxes are used to cut preexisting labor taxes. Country studies include; McKitrick (1997), Canada; Garbaccio, Mun and Jorgenson (1999), China; Edwards and Hutton (2001), UK; Ibarraran, Viniegra and Boyd (2001), Mexico; Roson (2003), Italy; and Takeda (2007), Japan.

In their review of country studies, Barker et al. (2007) conclude that the benefits associated with revenue recycling (replacing current taxes with revenues raised through climate policy) can be significant. Taken in combination with other ancillary benefits, this greatly expands the scope for low-cost and no-regrets outcomes. We return to this topic later in this section.

Another set of positive externalities, referred to collectively as co-benefits, include collateral health benefits that are realized when other types of pollutants are reduced together with greenhouse gases. Both top-down and bottom-up models have been employed to measure such effects. For example, Li (2002, 2006) looks at health benefits associated with greenhouse gas emissions in Thailand and Burtraw et al. (2003) examine the potential for positive health gains associated limits on US greenhouse gas emissions. Dudek., Golub and Strukova (2003), Dessus and O'Connor et al. (2003) and Aunan et al. (2003) examine the same issue in Russia, Chile and in China, respectively. A series of papers, including Gundimeda (2004), Plantinga and Wu (2003), Feng and Kling (2005), Yemshanov et al. (2005), look at forestry and carbon sequestration co-benefits. These benefits are tied to both the environmental services generated by sustained forests and incomes associated with payments for environmental services. Pendell et al. (2007) provide an example related to soil fertility.

In their synthesis, Barker et al. (2007) note that conservative studies of the ancillary health benefits associated with climate change policy can equal 30-50 percent of estimated mitigation costs, while some studies, especially studies of developing countries, indicate that health benefits can exceed mitigation costs. They also note that several studies suggest that a large share of business-as-usual emissions that can be reduced without welfare loss: 13-23 percent in India (Bussolo and O’Connor, 2001); 15-20 percent for China (O’Connor, 2003); and 20 percent for Chile (Dessus and O’Connor 2003). Other studies suggest savings could be had on other types of air pollution controls as well. For example, Burtraw et al. (2003) estimate that a 31 percent reduction in CO2 emissions in the United States would drive the price of SO2 permits to zero.

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_etc. to be paid by the bank ...conducts financial investigations on suspected fraud ... prepares and certifies financial statements for presentation to the board of directors, executives, shareholders ..._ Table 1 shows the coverage of the October Inquiry by occupation and country over time. In 1924 the survey gathered data on wages in 18 occupations in 15 countries. In ensuing years the ILO expanded the number of countries and occupations. Country coverage increases fairly steadily so that the 1983-99 Inquiry data files on which we focus had wage statistics for 158 countries in at least one year and wages for up to 76 countries in any given year. The number of occupations increased from 30 occupations in 1929, to 41 in 1951, to 48 in 1953, and then to 161 in 1983.<sup>4</sup> With respect to gender, the ILO October Inquiry reported wages for male earners for the period 1924-1952. In 1953 it changed the observation unit to adult workers, but with a gender breakdown in reported pay for 6 occupations. In each of the years in the period 1954-1982 there was a gender breakdown for between 6 and 12 occupations. After 1982 the number of occupations was expanded to 161, and for most of these occupations a gender breakdown and therefore gender gap was reported in any year.

If each country contributed information on wages from a nationally representative survey based on ILO definitions, the October Inquiry would be the ideal source for comparing the pay of male and female workers across countries and occupations.

However the October Inquiry data fall short of being ideal. Indeed, the problems involved are such that the Inquiry is one of the least used sources of cross-country data in the world (see Freeman and Oostendorp 2000, 2002).

The main problem is that countries respond to the ILO’s request for information often in inconsistent ways. Recorded wages are not directly comparable either between countries or in the same country over time, or between occupations in one country at a point in time. The recorded wages are non-comparable because countries report data from a variety of national sources rather than conducting special surveys to respond to the

> 4 Starting from 1983, the ILO actually asks for information on 159 occupations but it differentiates occupation 139, executives in the government into three sectors; national, regional or provincial, and local governments. The number of occupations was expanded over time by adding new occupations, while a few occupations were dropped. The definition of the individual occupations was changed in 1983 for the last time, but most pre-1983 occupations can be matched with the 1983-99 occupations. However because we only use the 1983-99 data there is no need to do this matching.

5
matriculation into public and private IHEs, the GPI was 1:3 and 1:4, respectively. The share of women admitted was considerably worse than the share of female high school graduates, as seen in Column 4 of Panels C and D. Finally, female applicants were significantly more likely to score lower than male test-takers among all applicants, as seen in Panel E, and among matriculated students, as seen in Panel

## F of Table 1.

Table 1: Descriptive statistics for Kankor exam participants between 2013-2018

|Mean|Standard|% female|/ female to|As a share of high|
|---|---|---|---|---|
|(1)|Dev.<br>(2)|male avg. <br>(3)|score ratio|school graduates<br>(Panel A) (4)|
|Panel A: High school graduates in _thousands_|||||
|Female<br>78.53|(9.77)||||
|Male<br>141.19|(15.13)||||
|Total<br>219.72|(24.49)|36%|||
|Panel B: Kankor test-takers/Applicants in _thous_<br><br>|_ands_<br>||||
|Female<br>62.24|(10.31)|||79%|
|Male<br>127.78|(19.22)|||90%|
|Total<br>190.02|(28.83)|33%||86%|
|Panel C: Newly admitted in public IHEs in _thou_<br>|_sands_<br>||||
|Female<br>14.64|(3.03)|||19%|
|Male<br>41.39|(1.35)|||29%|
|Total<br>56.04|(3.37)|26%||25%|
|Panel D: Newly admitted in private IHEs in _tho_|_usands_<br>||||
|Female<br>9.23|(1.83)|||12%|
|Male<br>35.99|(5.65)|||25%|
|Total<br>45.22|(7.47)|20%||20%|
|Panel E: Average score for Kankor applicants (0|-360)<br>||||
|Female<br>186.81|(44.66)||||
|Male<br>193.23|(48.43)||||
|Total<br>189.41|(50.44)|0.97|||
|Panel F: Average score for admitted students in|public IHE|(0-360)|||
|Female<br>235.66|(47.04)||||
|Male<br>236.47|(46.05)||||
|Total<br>236.26|(46.31)|0.99|||

Note: the raw data is compiled from multiple sources, mainly Afghanistan yearly statistics books published by the National Statistics and Information Authority (NSIA), Ministry of Education (MoE), and the Kankor results for 2013–2018.

# **3.2 Gender quota**

The gender quota for admission to public universities was first introduced in the 2016 academic year and gradually expanded until the Taliban returned to power in 2021. Female test-takers typically scored 10
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- [9] Christiano, L., Motto, R., Rostagno, M., 2004. The great depression and Friedman-Schwartz hypothesis. National Bureau of Economic Research Working Paper no. 10255.

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- [11] Detragiache, E., Tressel, T., Gupta, P. 2006. Foreign banks in poor countries: theory and evidence. IMF Working Paper WP/06/18.

- [12] Diamond, D.W., 1984. Financial intermediation and delegated monitoring. Review of Economic Studies 51, 393-414.

- [13] Diamond, D.W., Dybvig, P. H., 1983. Bank runs, deposit insurance, and liquidity. Journal of Political Economy 91, 401-19.

- [14] Diamond, D.W., Rajan, R. G., 2006. Money in a theory of banking. American Economic Review 86, 30-53.

- [15] Disyatat, P., 2008. Monetary Policy Implementation: Misconceptions and their Consequences. BIS working paper No. 269.

- [16] Drehmann, M., Goodhart, C., Krueger, M., 2002. Challenges to currency: will cash resist the e-money challenge?. Economic Policy, April.

- [17] Kashyap, A.K., Rajan, R., Stein, J.C., 2002. Banks as liquidity providers: an explanation for the coexistence of lending and deposit-taking. Journal of Finance 57, 33-73.

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19
# **4. A contemporary application: Explaining conflict**

One of the ways to look at the contemporary relevance of the inequality extraction ratio is to study its potential role in one of the areas where, on an _a priori_ grounds, it should matter, namely in the analysis of civil war and within-national conflict. As is well known, simple interpersonal inequality reflected in a Gini coefficient is seldom found to be a statistically significant determinant of conflict (see Collier and Hoeffler 2004; Collier, Hoeffler and Rohner 2008, p. 16; and review in Sambanis 2004) . This leads to a somewhat bizarre and counter-intuitive conclusion that inequality is not associated with conflict. More recently, other types of inequalities, most notably horizontal, that is, inequality in average incomes between groups, have gained prominence (Stewart 2000; Østby 2008; Cederman, Weidmann and Gleditsch, 2011). While in principle such inequality may be thought related to conflicts in multi-ethnic or multi-religious societies, it cannot capture inequality in societies that are homogeneous along these dimensions. For example, the civil war waged by the Khmer Rouge in Cambodia was dominantly politically-driven, not ethnic. So were the Great Leap Forward, the first civil war in Angola between the government and UNITA and a number of conflicts in Argentina and Colombia.

The inequality extraction ratio, by capturing how close to the frontier is actual inequality, conveys the information about the relative “rapaciousness” of the elite and combines in its formulation two aspects that are often found important for the explanation of civil conflict: the average level of development of a country (its GDP per capita) and its income distribution. To check the role of IER, we use a very detailed database on civil war created by Nicholas Sambanis (Sambanis and Schulhofer-Wohl, 2009). The database covers 151 conflicts in 70 countries over the period 1945-2002. This is probably the most complete data base of civil conflict: it treats as distinct the conflicts that might have overlapped in a given country over the same time period but were motivated by different reasons and had different actors; it includes the data on the duration of each conflict and its estimated casualties. Here we consider the role of IER in “explaining” the number of years of conflict per country and the overall casualty rate in the period 1960-2002. We exclude the pre1960s conflicts that were often driven by the decolonization movement and whose determinants differed from those of the post-1960s conflicts.

20
# **Structure of the Tunisian Market**

The Tunisian market comprises 22 companies. Of these, II engage in multi-branch operations, 4 are single branch companies (2 specialize in life insurance, I in export insurance and I in reinsurance) and 7 arc off-shore companies authorized to conduct operations w th nonresidents. In terms of legal status, 5 of the 15 resident companies are state-owned<sup>3</sup> , 7 are set up as joint stock companies (societes anonymes) and 3 are mutual companies. Excluding two state-owned companies that specialize in reinsurance and export insurance, the business of the remaining 13 companies is structured as shown in Table 2.

**Table 2**

|**M**|**arket Structure,**<br>1990<br>PREMIUMS<br>(MD)|**1990 and 1993**<br>%|1993<br>PREMIUMS<br>(MD)|%|
|---|---|---|---|---|
|STAR|62.1|36.0|86.8|33.2|
|EL ITTIHAD|13.4|7.8|24.4|9.3|
|LLOYD TUNISIEN|8.3|4.8|11.7|4.5|
|PUBLIC SECTOR|83.8|48.9|122.1|47.1|
|GAT|20.1|11.6|30.3|11.6|
|COMAR|17.9|10.4|30.4|11.6|
|ASTREE|14.9|8.6|20.6|7.9|
|MAGHREBIA|11.3|6.5|20.5|7.8|
|CARTE|8.4|4.9|12.7|4.9|
|HAYETT|0.7|0.4|2.0|0.8|
|AMINA|0.8|0.5|1.1|0.4|
|PRIVATE SECTOR S.A.|74.1|42.9|117.6|45.0|
|CTAMA (Agricultural)|7.6|4.4|10.8|4.1|
|MGA (Agricultural)|4.1|2.4|5.6|2.1|
|MAE (Teachers)|3.1|1.8|4.3|1.6|
|PRIVATE SECTOR MUTUAL|14.8|8.6|20.7|7.9|
|TOTAL|172.8|100.0|261.2|100.0|
|CONCENTRATION C3|100.1|58.0|147.5|56.5|
|HHI|1789||1654||

Source: Ministry of Finance, Direction Generale des Assurances and F.TU.S.A.

El Ittihad, which is owned by the trade unions, is officially classified as a mutual company. In practice, however, it appears to be heavily supported by capital injections or at the very least implicit guarantees from the state.

3
transformed a highly centralized government to one that gave broad autonomy to the regions in most domains. We use nationally representative data on health and education services gathered in 2006 from the second round of the Governance and Decentralization Survey (GDS-2), which contains detailed questions related to governance and service delivery. The survey collected data on satisfaction from households _and_ information on objective quality directly from facilities.

In addition to the methodological question of whether satisfaction surveys yield useful results on facility quality, the findings of this paper also have more direct implications for policymakers in Indonesia. Our analysis of the determinants of satisfaction among service users suggests that users value certain dimensions of “quality” in public services (health and education) more than others, and that these determinants of satisfaction vary between rich and poor districts. This information is likely to be useful to inform policies engaged to improve basic services, well beyond what generic and aggregated measures of satisfaction typically provide.

Section II explains the motivation for this study, examining the limitations of satisfaction surveys and outlining some of the concerns this paper seeks to address. Section III describes the dataset used for our analysis and the model used. In Section IV, we describe the models and the results on the determinants of satisfaction with both health and education facilities. Section V discusses the implications of our results for policy and the design of satisfaction surveys.

3