rafmacalaba/datause-encoder-data huggingface dataset:
Ong, Hwee Teng. 2002. “Sustaining Singapore’s Productivity Growth”, _Productivity Digest July 2002._ Spring Singapore.

Phang, Sock-Yong, 2003. “Strategic Development of Airport and Rail Infrastructure: The Case of Singapore”, _Transport Policy_ 10 (2003), Pergamon.

Rao, B.V.V. and C. Lee, 1996. “Sources of Growth in the Singapore Economy and its manufacturing and Services Sectors,” _The Singapore Economic Review_ , Vol. 40, No.1, 83-115.

Stern, Scott, Michael porter and Jeffrey Furman, 2000. “The Determinants of National Innovative Capacity”, _NBER Working Paper_ 7876.

Wan, David, Chin Huat Ong and Francis Lee (2003). Determinants of firm innovation in Singapore. _Technovation_ (forthcoming).

Wong, Poh Kam, 2003. “From Using to Creating technology: The Evolution of Singapore’s National Innovation System and the Changing Role of Public Policy”, _World Bank institute Working Paper 37221_ . The World Bank.

Wong Poh Kam, Finna Wong, Lena Lee and Yuen Ping Ho, 2004 (a). “Global Entrepreneurship Monitor: GEM Singapore 2003.” NUS Entrepreneurship Center.

Wong Poh Kam, Yuen Ping Ho, Annette Singh, 2004 (b). “Singapore as an Innovative City in East Asia”, mimeo.

World Development Report. 2004. The World Bank.

World Economic Forum (WEF), 2002. _Global Competitiveness Report_ . Geneva.

Wu, Wei Lin (2003). “Educational Upgrading through Private Educational Institutions”, Statistics Singapore Newsletter.

Wu, Wenbo and Otto A. Davis (2003). Economic Freedom and Political Freedom. Forthcoming in _Encyclopedia of Public Choice_ .

Young, Alwyn. 1992. “A Tale of Two Cities: Factor Accumulation and Technical Change in Hong Kong and Singapore”, in Olivier Jean Blanchard and Stanley Fischer, eds., _NBER Macroeconomics Annual 1992_ . Cambridge, MA: MIT Press.

Young, Alwyn. 1995. “the Tyranny of Numbers: Confronting the Statistical realities of the East Asian growth Experience”, _Quarterly Journal of Economics,_ August 1995.

38
Policy Research Working Paper 4816

# **Abstract**

This paper examines the impact of free trade agreement (FTA) use on import prices. For this analysis, it employs establishment-level import data with information on tariff schemes, that is, the FTA and most-favored-nation schemes used for importing. Unlike previous studies, this paper estimates the effects of FTA use on prices by controlling for differences in importing-firm characteristics. There are three main findings. First, the effect of FTA use is overestimated when not controlling for importing firm-related fixed effects. Second, on average, firms’ FTA use reduces tariffs by 12 percentage points and raises import prices by 3.6–6.7 percent. Third, in general, a price rise resulting from the costs of complying with rules of origin was not found.

This paper is a product of the Strategy and Operations Team, Development Economics Vice Presidency. 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://www.worldbank.org/ research. The authors may be contacted at kazunobu_hayakawa@ide.go.jp.

_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
MoEF, 2009. Bangladesh Climate Change Strategy and Action Plan 2009. Ministry of Environment and Forests, Government of the People’s Republic of Bangladesh, Dhaka, Bangladesh.

Quasem, M. A. 1992. Economic situation in ecologically favorable and non favorable areas. The Bangladesh Development Studies, XX(4), 1–14.

Reardon, T., Julio Berdegué, Christopher B. Barrett, and Kostas Stamoulis 2006. “Household Income Diversification into Rural Nonfarm Activities” in Steven Haggblade, Peter Hazell and Thomas Reardon, editors, _Transforming the Rural Nonfarm Economy,_ Johns Hopkins University Press, Baltimore.

Rosenzweig, M.R., and H.P. Binswanger. 1993. Wealth, Weather Risk and the Composition and Profitability of Agricultural Investments. _The Economic Journal_ , 103, no. 416: 56–78.

World Bank (2008). Poverty Assessment for Bangladesh: Creating Opportunities and Bridging the EastWest Divide. Report No. 44321-BD. Washington DC.

Yu, W., J. Thurlow, M. Alam, A. Hassan, A. S. Khan, A. Ruane, C. Rosenzweig, 2010 _Climate Change Risks and Food Security in Bangladesh_ . London: EarthScan.

22
are shown.<sup>20</sup> In the pooled model, the only variables that are significantly different from zero are age, holding a teaching certification, and being born in the (local) district, with post-FPE teachers being older by 2.3 years, 5 percentage points less likely to hold a certification, and 8 percentage points more likely to be born in the district. The positive age effect is also apparent in three of the six country-specific sets of estimates (with a similar magnitude of close to 3 years in Kenya, Madagascar, and Tanzania). The teaching certification effect has the same negative sign in Madagascar, Mozambique, and Togo, although none of the country-specific estimates are statistically significant. The locally born effect has the same negative sign in Madagascar, Mozambique, Tanzania, and Uganda, although it is only statistically significantly different from zero in the latter. Perhaps surprisingly, given that much of the narrative around the hiring of teachers at the time of FPE suggests a lowering of educational standards, the results do not suggest that post-FPE teachers (still working in grade 4 classrooms “today”) are less likely to have at least a secondary education, at least a diploma, or at least a bachelor’s degree. On the latter there is some degree of consistency that post-FPE teachers are slightly less likely to have a bachelor’s degree—but the coefficient estimates are small and far from statistically significant at conventional levels. The results do not suggest that there is a difference in the contract status of teachers hired before and after FPE.

The age and education qualification results are somewhat counter to the common narrative that FPE resulted in the recruitment of young and un(der)-educated teachers. It is possible that countries may have sought to also recruit older people, with basic general education qualifications, who were in other professions, and who were local. The certification result is more consistent with the common narrative, although the country estimates suggest that it is only in Mozambique where the effect is substantively large (albeit statistically insignificant).

# 4.4 Classroom observation and teacher absence

The last set of results comes from the analysis of the classroom observation and teacher absence data.<sup>21</sup> There is no consistent evidence that teachers hired after FPE do any worse on any of these

> 20 A bandwidth of 7 was chosen to report here for parsimony and because it is a relative midpoint. Results for bandwidths of 5 and 10 years are reported in Appendix Table 6.

> 21 Results for bandwidths of 5 and 10 years are reported in Appendix Table 7.

14
<!-- Start of picture text --> 30<br>25<br>20<br>x<br>> 15<br>fo}<br>z=<br>2<br>@ 10<br>c<br>2<br><5&<br>£<br>0<br>2016 2017 2018 2019 2020 21<br>5<br>-10<br>=——— CPlinflation =—=—=EPlinflation << <=PePI inflation<br><!-- End of picture text --> <!-- Start of picture text --> 124<br>122<br>120<br>118<br>116<br>114<br>112<br>110<br>108<br>106<br>104<br>2012 2013 2014 2015 2016 2017 2018 2019 2020<br>eeeeSabah —==Selangor —==—Terengganu<br><!-- End of picture text -->
_Bank ownership and structure and crises_ The nature of bank ownership, whether private or public, domestic or foreign, has been found to have a strong association with various aspects of bank performance. Does the likelihood of a systemic banking crisis also depend on who owns the banks?

State ownership of banks, although declining, continues to be popular in many countries, despite widespread evidence of political abuse and governance problems in stateowned institutions (World Bank, 2001). La Porta, Lopez-de-Silanes and Shleifer (2002) and Barth, Caprio and Levine (2001) find that greater state ownership in banking is associated with reduced competition, poorer productivity and lower growth. Concerning systemic crises, Caprio and Martinez-Peria (2000) show that greater state ownership at the beginning of the 1980s is associated with a greater probability of a banking crisis during 1980–97. Using simple cross-sectional regressions, Barth, Caprio and Levine (2001) confirm this finding.

Whether developing countries should welcome foreign ownership of banks is also a highly disputed issue, particularly as the share of banking assets controlled by foreign banks soared in Africa, Latin America, and Eastern Europe in recent years (World Bank, 2001). Empirical studies have shown that by improving overall operating efficiency, foreign entry helps create the conditions for improved financial intermediation and long-term growth (Claessens, Demirgüç-Kunt and Huizinga, 2001).

On systemic fragility, one concern is that foreign banks may not have a lower longterm commitment to the host country and might flee at the first signs of trouble. Even worse, they may introduce a new source of contagion by withdrawing from the host country when conditions in their home country deteriorate. Existing empirical evidence does not support these concerns. Demirgüç-Kunt, Levine, and Min (1998) find that the presence of foreign banks is associated with a lower risk of banking crisis. Dages _et al_ . (2000) find that foreign banks operating in Argentina and Mexico had stronger and less volatile loan growth than 18
# **Appendix S2. Robustness tests for the poverty-food price regressions**

# **Table S2.1 Re-estimating the core results with the robust regressor**

|Regression Number|2|4|
|---|---|---|
|Estimator|Robust|Robust|
||$1.25/day<br>poverty|$2/day<br>poverty|
|Change in log of domestic food prices|-29.34***|-21.69***|
||(6.02)|(6.56)|
|R-squared|0.12|0.07|
|N|302|313|

Source: Author’s estimates.

Notes: See text for definitions of the variables. *, ** and *** indicate significance at the 10%, 5% and 1% levels respectively. Regressions are estimated using the _rreg_ command in STATA.

25
<mark>overwhelmingly procyclical, especially among African countries. Dabla-Norris, Minoiu, and Zanna (2010) find that bilateral aid flows are on average procyclical with respect to the business cycles in both donor and recipient countries; however, they also find that these flows become countercyclical when recipients face large adverse terms-of-trade shocks, thereby playing an important buffering role during downturns.</mark> <mark>It appears that no assessments of the cyclicality of private sector-focused impact investing by IFIs have yet been undertaken. This study seeks to fill that gap in the empirical literature by assessing</mark> the cyclicality of capital flows of IFC as the largest global development finance institution with a private sector focus <mark>and how the cyclical patterns of IFC investments in countries and regions are related to its portfolio asset quality and profitability. I</mark> n turn, the relation between IFC cyclical patterns and its financial performance would help assess the feasibility of a less procyclical investment strategy, particularly during downturns.

# **3 Empirical Approach**

## **3.1 IFC Investment Activity**

The study uses two different variables to model IFC investment activity: (i) _original commitments_ , which represent the IFC’s initial legal obligation to provide financial products to the client for a given period and (ii) _disbursements_ , which are principal outflows from the IFC to the client under the relevant investment agreement. It should be noted that commitments and disbursements data include both equity and debt<sup>4</sup> financing. The data also aggregates across long-term financing (LTF), short-term financing (STF), and guarantees. It should be noted that STF and guarantees, given their structure and tenor, do not disburse, therefore they are included only in commitments.<sup>5</sup> We differentiate commitments and disbursements, as the former denote more the moment of the IFC investment decision, while the latter are more related to the client’s decision to request a

> recipient countries. Burnside and Dollar (2000) show that aid accelerates growth if a sound policy framework is in place. Hansen and Trap (2000) determine that the growth effect of aid is significant but not linear. Easterly et al. (2004) contend that Burnside and Dollar’s finding that aid positively affects growth is not robust to the inclusion of new data. More recently, Andersen et al. (2020) demonstrate that a share of aid is diverted to private bank accounts in offshore financial centers, indicating that elite aid-capture reduces the impact of aid on growth.

> 4 Over 80 percent of commitments and disbursements data for the study’s sample countries is in debt.

> 5 Over 60 percent of commitments and over 90 percent of disbursements data for the study’s sample countries is in long term financing instruments.

6
Muslim countries that leave to Islamic tribunals the regulation of Muslim minorities (India, Pakistan, Bangladesh, Egypt), and countries that are considering recognizing the authority of religious tribunals (U.K., Canada).

# **References**

Arnold, F. (1997) “Gender Preferences for Children”. _Demographic and Health Surveys Comparative Studies_ . 23:1–56.

Basu, D. and R. De Jong (2010) “Son Preference and Gender Inequality”. _Demography_ . 47: 521-536.

Borooach, V., Q.T. Do, S. Iyer and S. Joshi (2009) “Missing Women and India’s Religious Demography”. _The World Bank, Policy Research Working Paper_ . 5096.

Bowen, J. (1996) “Equality, Difference, and Law in Indonesian Inheritance Practices: A Sumatran Case Study”. _Political and Legal Anthropology Review_ . 19 (1): 83-90.

Buchanan, K (2010) “ _Indonesia: Inter-Religious Marriage_ ”. The Library of Congress.

Butcher, K. and A. Case (1994) “The Effect of Sibling Sex Composition on Women's Education and Earnings”. _Quarterly Journal of Economics_ . 109(3): 531-563.

Cammack, M. (1999a) “Islamic Inheritance Law in Indonesia: The influence of Hazairin’s Theory of Bilateral Inheritance”. In: Lindsey, T. (Ed. ) “ _Indonesia, Law and Society_ ”. Federation Press.

Cammack, M. (1999b) “Inching Toward Equality: Recent Developments in Indonesian Inheritance Law”. _Indonesian Law & Administrative Review_ . 5(19).

Cammack, M. and T. Heaton (2002) “Regional Variation in Acceptance of Indonesia’s Family Planning Program”. _Population Research and Policy Review_ . 20: 565-585.

Cammack, M. (2007) “Islamic Inheritance”. In: Clark, D. S. (Ed.) “ _Encyclopedia of Law and Society: American and Global Perspectives_ ”. Sage Publications.

27
exposure and infrastructure disruptions. In order to overcome such distortions, regressions can be used that control for industry- and city-level fixed effects and several other firm characteristics. Table 1 summarizes the results of three weighted regressions with such controls that include standard errors clustered at the city-level. Overall, one main message emerges: system-wide disruptions are more important than individual firm-level characteristics. We interpret this as the ripple effect of floods dominating the direct effects, i.e., whether a firm is directly affected by a flood only marginally contributes to the costs that floods it already faces through system wide network disruptions.

Table 1: Results from weighted OLS regression, city-level normalized survey stratification weights applied. Standard errors in italics, clustered on cities. Abidjan city-level fixed effects omitted to allow estimation of model. Significance levels: *** 0.01, ** 0.05, * 0.10.

|Dependent:|Blackouts|Water disruptions|Transportproblems|
|---|---|---|---|
|Firm age|0.217|8.145**|-0.001|
|_years of official registration_|_(1.46)_|_(2.89)_|_(0.00)_|
|Employment|-0.912*|0.494|0.001|
|_number of full time employees_|_(0.50)_|_(0.90)_|_(0.00)_|
|State ownership|3.128|-0.656|0.015|
|_in %_|_(5.81)_|_(7.00)_|_(0.02)_|
|Export orientation|-0.214|4.232|-0.000|
|_% of total sales_|_(1.45)_|_(3.69)_|_(0.00)_|
|Generator ownership|69.452|126.011|0.054|
|_Dummy_|_(50.81)_|_(289.08)_|_(0.15)_|
|Distance to city centre|-0.001|0.008|-0.000|
|_At the ward-level, in meter_|_(0.00)_|_(0.01)_|_(0.00)_|
|Flood-threatened|28.583|54.883|0.150|
|_Dummy_|_(70.41)_|_(262.29)_|_(0.14)_|
|ISIC Sector Fixed Effects|YES|YES|YES|
|Accra|519.455***|212.819|-0.875***|
|_City-level fixed effect_|_(53.64)_|_(170.65)_|_(0.05)_|
|Addis Ababa|185.962***|-189.789*|-1.629***|
|_City-level fixed effect_|_(56.07)_|_(87.65)_|_(0.07)_|
|Bamako|-140.272*|-539.146***|-0.131|
|_City-level fixed effect_|_(68.80)_|_(101.07)_|_(0.08)_|
|Cotonou|941.516***|-530.813***|-0.871***|
|_City-level fixed effect_|_(64.91)_|_(81.03)_|_(0.06)_|
|Dar es Salaam|710.536***|-83.131|-0.568***|
|_City-level fixed effect_|_(57.76)_|_(89.47)_|_(0.04)_|
|Douala|338.875***|-334.603***|-0.817***|
|_City-level fixed effect_|_(62.92)_|_(64.68)_|_(0.06)_|
|Free Town|705.323*|-1568.848|-0.631|
|_City-level fixed effect_|_(332.75)_|_(1738.63)_|_(0.49)_|
|Kampala|362.801***|-588.947***|-1.097***|
|_City-level fixed effect_|_(41.15)_|_(158.44)_|_(0.04)_|
|Kigali|-62.963|-392.183***|-1.045***|
|_City-level fixed effect_|_(43.32)_|_(79.57)_|_(0.05)_|
|Monrovia|282.523***|3.248|-0.500***|

12
This linkage between corruption, weak institutions, and offshores was also confirmed in a crossnational study of petroleum rents. Andersen et al. (2016) found that petroleum rents originating in countries with weak institutions (mostly autocracies) have a much higher probability of ending up in tax havens than those originating in non-autocracies. The authors suggest that “unanticipated increases in petroleum rents are partly captured by political elites and transferred to private bank accounts in havens, either directly or through sham corporations based in other havens” (Andersen et al. 2016, 28). They find a similar pattern at work in these polities in the face of political instability: elites transfer part of their domestic wealth to tax havens prior to elections and coups d’etat (Ibid.). Besides petroleum rents, offshores enable laundering the proceeds from other types of corruption and illicitly obtained wealth. Another recent study by Andersen et al. (2020) reveals that foreign aid disbursements from the World Bank and the Bank for International Settlements to poor countries coincide with significant increases in the value of bank deposits in secrecy jurisdictions. This study suggests that foreign aid might be diverted by economic and political elites into privately held accounts in jurisdictions that enable anonymity and non-transparency, specifically places like Zurich, a wellknown center for private wealth management (Ibid., 3).

The link between political instability and capital flight to secrecy jurisdictions is confirmed by the study of the patterns of financial flows in Ukraine. Earle et al. (2019) reveal that the Ukrainian oligarchs who are better connected politically tend to be more secure about their assets relative to those less connected (or associated with the competing political group). Their perception of the security of their assets is demonstrated by the wealth-hiding patterns: those less politically connected tend to use secrecy jurisdictions to a greater degree than the rest of the oligarchs. Ukraine’s 2004 Orange Revolution that resulted in the competing political group coming to power provided a context approximating a natural experiment that enabled this team of researchers to trace the causal linkages between the degree of political connections and a pattern of reliance on tax havens to hide wealth. This study is an important addition to the literature that goes beyond treating offshores as tax minimization vehicles.

The policy makers’ agenda on secrecy jurisdictions and investment round-tripping is frequently dominated by discussions that emphasize tax avoidance issues and build on concern over public finances and collective welfare. The additional rationale motivating the reliance on these jurisdictions 14
# **A. Controlling for Entry**

The ideal empirical tests would benchmark the performance of NBC and NMB over time relative to that of a static group of banks of the same ownership type. However, a quick glance at Table 3 indicates that there was substantial net entry during our sample period for foreign and private domestic banks. Those figures mask other changes in the roster of banks: six small banks were liquidated, and two mergers were consummated involving five banks. All of these cases affect the composition of the group of private domestic banks, our omitted category, and thus potentially affect the comparisons that we make between private banks, NBC, and NMB in the base regressions.

We think this unlikely because the regression results and figures conform so well to the narrative description of the privatization, but it is possible. We therefore create new categories of banks to perform our robustness checks. The first three are for banks that appeared in the sample in all quarters, one for private domestic ( _Private full sample_ ), foreign ( _Foreign full sample_ ), and state banks ( _State full sample)_ . The next three are for new entrants, one for each type of ownership ( _private entry, foreign entry, state entry_ ). These dummy variables equal one from the time the bank enters the sample. For each type of entrant we also include a variable for the time since entry ( _e.g., Quarters since Private Entry)_ to capture dynamic performance effects. A seventh category is for banks that are liquidated; the corresponding variable ( _Liquidated_ ) equals one until the bank leaves the sample.

The final category is for banks that were involved in mergers or acquisitions. We follow the method in Berger et al. (1998) by combining the pre-merger financial data for all banks that would eventually be party to the merger/acquisition to create a pro-forma bank.<sup>28</sup> We can therefore test whether the performance of the same pool of banking assets was managed better after merger/acquisition. We do so by including a dummy variable for the two pro-forma banks that equals one throughout the sample ( _Selected for Merger_ ), another equal to one beginning at the time of the merger event ( _At Merger_ ) to capture the initial effects of combining the banks and their balance sheets, and another equal to the number of quarters since the merger ( _Time Since Merger_ ) to capture dynamic postmerger performance effects. These bank ownership categories therefore enable us to fully

> 28 This reduces the number of observations in the regressions from 908 to 866.

19
**Figure 2: Bank assets in the** 1990s

<!-- Start of picture text --> Ratio of banidng sector assets to GDP: Ratio of banking sector assets to GDP:<br>Argentina Chile<br>59 19i0 160% 99<br>541/. 140%e<br>53%-1/620o<br>57% /<br>51% /80Y.<br>501/6- / 60%/.<br>4911.o/ 40%-<br>43% _ 20_/6<br>19 98 1999 2000 1996 1997 1998 1999 2000<br>36%~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~0/<br>331/6 _37501/.<br>33%<br>33% 1<br>32P/o 3 7.W/.%<br>32%9 1998 1999 2000 3 0 99 1999 2000<br><!-- End of picture text --> 30