rafmacalaba/datause-encoder-data huggingface dataset:
# **3.3 Representativeness and Weighting**

The HFPS surveys are not nationally representative at either the household or individual level. Only households where a member owned a phone, had access to electricity and mobile network coverage as well as was willing to participate were interviewed. To partially address this, most surveys adjusted the household sample weights to account for the non-random selection of households.<sup>5</sup> Questions of representativeness at the individual level are more serious, because many surveys drew their sample from an existing pre-pandemic survey, and these explicitly sought to interview heads of households or their spouses. For these surveys, we therefore mainly observe the labor market outcomes of household heads. We observe data on relation to head in 20 countries, which unfortunately excludes the surveys from LAC, which did not collect this information. In these 20 countries, 67 percent of the sample are heads (vs 23 percent in the GMD), 18 percent are spouses (vs 17 percent in the GMD), and 11 percent (vs 44 percent in the GMD) are children. To the extent that heads have different labor market outcomes than others in the households, the phone surveys that explicitly sought to interview heads will present a biased picture of labor market outcomes.

Selection bias in labor market outcomes is a particular concern when comparing labor market outcomes in Sub-Saharan Africa to those in Latin America & the Caribbean, for two reasons.<sup>6</sup> First, the surveys in LAC were conducted through random digit dialing rather than recontacting households interviewed in an existing survey. The latter sampling strategy usually sought to re-interview household heads while the former did not. As mentioned above, this means that the surveys outside LAC are highly skewed towards heads. Second, the

> 5The only surveys that did not use household weights were those from Poland and South Sudan.

> 6Within-household decisions, such as between the head and non-head of the household, on labor market participation and labor supply may also be important. There may also be differences in the labor supply elasticities between the household heads and non-household heads. As McKenzie (2004) in his study of a sharp economic contraction points out, labor supply is generally considered to be more elastic for women and young adults than prime-age males. One would expect a larger supply response from these groups, especially if they are non-household heads. This in turn could have an effect on potentially underestimating the employment effects in SSA, with data based mainly on household heads, presumably prime-age males.

14
military and police resources simply to control<sup>society and monitor social activity. In circular fashion,</sup> concentrating on coercion and control,<sup>rather then consensus, may affect development effectiveness,</sup> lowering economic performance, and<sup>making legitimacy even more difficult to establish (p. 10).</sup> Governance based on personal loyalties,<sup>patron-client ties, appeals to particular ethnic groups,</sup> or through the "purchase" of allegiance offers<sup>only limited legitimacy. Regimes with low legitimacy are</sup> more subject to the frequent use of force,<sup>for citizens are apt to challenge the government through riots,</sup> demonstrations, and strikes (Avery 1988: 113).<sup>Their military budgets may absorb a large portion of</sup> the nation's scarce resources -- and often for<sup>use against their own people. The absence of legitimacy</sup> occasions instability and eventually may lead<sup>to violent overthrow of the government. In systems with</sup> high legitimacy, citizens may be more willing<sup>to save, to defer gratification, and to accept unpopular</sup> government decisions in the belief that the<sup>government is acting in their interests.</sup>

# B. **Participation, Institutional Pluralism,**<sup>**and Economic Performance**</sup>

Are participation and institutional pluralism related<sup>to economic performance? Some evidence suggests</sup> a correlation between popular participation and broad-based<sup>growth. Morris and Adelman's (1989)</sup> extensive study of nineteenth century development<sup>examined 35 institutional and economic variables for</sup> 23 countries, comparing paths of development<sup>from 1850-1914. Empowerment and participation figured</sup> strongly in the second of their two generalizable<sup>findings: "Progressive agriculture is necessary (but not</sup> sufficient) to sustained industrialization; increased<sup>political power to nonelite groups is essential (but not</sup> sufficient) to government policies that spread growth<sup>widely" (p. 1428).</sup> Huntington and Nelson (1976) introduced<sup>some complications into these findings in their</sup> argument that effective land reform, one of the<sup>key components to later economic equality, is best</sup> introduced under "noncompetitive and nondemocratic<sup>governments," i.e., those with low participation.</sup> 32
- Engel, C., Matsumoto, A., 2009. The International Diversification Puzzle When Goods Prices Are Sticky: It’s Really about Exchange-Rate Hedging, Not Equity Portfolios. American Economic Journal: Macroeconomics 1, 155–88.

- Greenwood, J., Hercowitz, Z., Huffman, G.W., 1988. Investment, capacity utilization, and the real business cycle. The American Economic Review , 402–417.

- Guiso, L., Sapienza, P., Zingales, L., 2013. Time varying risk aversion. Technical Report. National Bureau of Economic Research.

- Hale, G., Obstfeld, M., 2016. The euro and the geography of international debt flows. Journal of European Economics Association 14(1), 115–144.

- Haselmann, R., Herwartz, H., 2010. The introduction of the euro and its effects on portfolio decisions. Journal of International Money and Finance 29, 94–110.

- Hobza, A., Zeugner, S., 2014. Current accounts and financial flows in the euro area. Journal of International Money and Finance 48, 291–313.

- Kalemli-Ozcan, S., Papaioannou, E., Peydr ́o, J.L., 2010. What lies beneath the euro’s effect on financial integration? Currency risk, legal harmonization, or trade? Journal of International Economics 81, 75–88.

- Lane, P., Milesi-Ferretti, G.M., 2005. The International Equity Holdings of Euro Area Investors. The Institute for International Integration Studies Discussion Paper Series iiisdp104. IIIS.

- Lane, P.R., 2006. Global Bond Portfolios and EMU. International Journal of Central Banking 2.

- Schmitt-Groh ́e, S., Uribe, M., 2003. Closing small open economy models. Journal of International Economics 61, 163–185.

- Spiegel, M.M., 2009. Monetary and financial integration: Evidence from the EMU. Journal of the Japanese and International Economies 23, 114–130.

- Tille, C., van Wincoop, E., 2010. International capital flows. Journal of International Economics 80, 157–175.

21
Table 4: First Stage Instrumental Variable Regressions

|Dependent variables|AV|E<br>|AVE+Tari¤|AV|E<br>|AVE+Tari¤|
|---|---|---|---|---|---|---|
||(1)<br>|(2)<br>|(3)|(4)<br>|(5)<br>|(6)|
|Average AVE of exporter|0.634***|0.608***||0.650***|0.626***||
||(0.030)|(0.031)||(0.030)|(0.024)||
|Tari¤||0.025***<br>|||0.024***<br>||
|||(0.004)|||(0.004)||
|Average AVE of exporter|||0.986***|||0.982***|
|+Tari¤|||(0.018)|||(0.018)|
|SPS/TBT NTMs|||6.907***|||6.829***|
||||(0.369)|||(0.368)|
|Other NTMs|||-0.321|||-0.271|
||||(0.445)|||(0.450)|
|Importer Fixed E¤ects|Yes|Yes|Yes|Yes|Yes|Yes|
|Exporter Fixed E¤ects|Yes|Yes|Yes|Yes|Yes|Yes|
|Product Fixed E¤ects|Yes|Yes|Yes|Yes|Yes|Yes|
|F-Statistics|441.13|392.79|2938.74|472.38|419.60|2850.57|
|Observations|256,711|250,432|153,084|251,934|245,615|150,582|

Notes: Robust standard errors in parentheses are clustered by importer-product;

*, ** and *** indicate that coe¢ cients are signi...cant at 90%, 95% and 99%, respectively.

Table 5: Second Stage Instrumental Variable Regressions

|Dependent variables|Quant|ity Discrep|ancies|Valu|e Discrepa|ncies|
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|AVEborder|1.257***|1.456***||1.354***|1.537***||
||(0.218)|(0.234)||(0.208)|(0.222)||
|tari¤||0.805***|||0.682***||
|||(0.0427)|||(0.0436)||
|avetar|||0.890***|||0.798***|
||||(0.0525)|||(0.0532)|
|SPS/TBT NTMs|||-9.221***|||-8.764***|
||||(1.302)|||(1.272)|
|Other NTMs|||-3.621***|||-3.598***|
||||(1.267)|||(1.256)|
|Observations|256,711|250,432|153,084|251,934|245,615|150,582|
|Importer Fixed E¤ects|Yes|Yes|Yes|Yes|Yes|Yes|
|Exporter Fixed E¤ects|Yes|Yes|Yes|Yes|Yes|Yes|
|Product Fixed E¤ects|Yes|Yes|Yes|Yes|Yes|Yes|

Notes: Robust standard errors in parentheses are clustered by importer-product;

*, ** and *** indicate that coe¢ cients are signi...cant at 90%, 95% and 99%, respectively.

42
<mark>WPS3544</mark>

# Learning-by-Doing, Learning-by-Exporting, and Productivity: Evidence from Colombia*

Ana M. Fernandes Alberto E. Isgut The World Bank Wesleyan University

**Abstract:** The empirical evidence on whether participation in export markets increases plantlevel productivity has been inconclusive so far. We explain this inconclusiveness by drawing on Arrow's (1962) characterization of learning-by-doing, which suggests focusing on young plants and using measures of export experience rather than export participation.  We find strong evidence of learning-by-exporting for young Colombian manufacturing plants between 1981 and 1991: total factor productivity increases 4%-5% for each additional year a plant has exported, after controlling for the effect of current exports on total factor productivity.  Learning-byexporting is more important for young than for old plants and in industries that deliver a larger percentage of their exports to high-income countries.

_Key Words_ : learning, trade, total factor productivity, exports, export-led growth

## _JEL Classification_ : D21, F10, L60

* We thank Eduardo Engel, Mike Lovell, and seminar participants at the 2004 Canadian Economic Association meetings and at Wesleyan University for comments, and Gustavo Hernandez and Fernando Mesa from Colombia’s Dirección Nacional de Planeación for providing Colombia’s input-output matrices.  The findings expressed in this paper are those of the authors and do not necessarily represent the views of the World Bank. Please address correspondence to Ana Fernandes, Development Research Group, The World Bank, 1818 H Street, N.W., Washington, DC 20433, USA, email: afernandes@worldbank.org.
It is also worth noting that Bancassurance is this development channel, whether or not the insurance company is a wholly owned bank subsidiary. Almost always the bank and the insurer will be different legal entities. Sometimes the bank will own the insurer (and, rarely, the insurer may own a bank). Often the bank will not own the insurer—and often the virtues of diversifying the risk will mean that some banks prefer not to own the insurer. So there is nothing intrinsic within the term Bancassurance that implies linkage in ownership terms between bank and insurer.

# **Bancassurance—The Potential**

Bancassurance has had important success in some economies and really quite limited success in other economies. It will be worth reviewing where it has worked well, and contrasting that with countries where it has not worked well, to give some answer to the question ―What is the potential of Bancassurance?‖

# **Where Bancassurance Has Shown Important Growth**

Table 1.1 sets out those countries where the market share of insurance placed through Bancassurance has shown important growth and exceeds either 40 percent (for Life business) or 10 percent (for non-Life business). Data are the most recently available as of 2007; sources are insurance regulators, insurance associations, Axco, Limra, and Swiss Re estimates.

**Table 1.1 Countries Where the Bancassurance Market Share Has Shown Important Growth and Exceeds 40 Percent (Life) or 10 Percent (Non-Life)** **_percent_**

|Country|Bancassurers’ Life Share|Bancassurers’ Non-Life Share|
|---|---|---|
|Australia|43|Verysmall|
|Belgium|48|6|
|Brazil|55|13|
|Chile|13|19|
|France|64|9|
|Italy|59|2|
|Malaysia|45|10|
|Portugal|88|10|
|Spain|72|7|

# Source:Authors

The penetration into Life insurance sales in many of these countries has been spectacular. Chile is quite unusual in that there has been greater success in non-Life than in Life with Bancassurance penetration. But in Brazil, France, Italy, Portugal, and Spain, the use of Bancassurance sales techniques has literally transformed the 9
Policy Research Working Paper 10135

# **Abstract**

Child marriage has lasting negative health, human capital, and welfare consequences. Conflict settings are characterized by a number of complex changes that can potentially increase the risk of child marriage, but there has been limited population-based research directly estimating the relationship between conflict and child marriage. Using Demographic and Health Survey data from 19 conflict-affected countries, this paper estimates the relationship between conflict and child marriage. It identifies the relationship based on variation over space and time in conflict intensity. The findings are mixed; in some countries conflict is associated with an increase in child marriage, in others it is associated with a decrease in child marriage, and in some cases there is not a statistically significant relationship. This overall pattern is robust to a variety of approaches to measuring conflict. These findings underscore how efforts to reduce child marriage need to consider conflict as a potential risk factor, but also one that is likely to interact with local economic, social, and demographic environments.

This paper is a product of the Gender Global Theme. 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/prwp. The authors may be contacted at darango@worldbank.org; cgkrafft@stkate.edu; jkelly@hsph.harvard.edu; and amalia.h.rubin@gmail.com.

_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
Detragiache, E. and A. Spilimbergo, 2002, Empirical models of short-term debt and crises: Do they test the creditor run hypothesis?, _IMF Working Paper 01/2_ Dewatripont, M. and E. Maskin, 1995, Credit and efficiency in centralized and decentralized economies, _Review of Economic Studies_ 62, 541-555

> Diamond, D., 1991, Debt maturity structure and liquidity risk, _Quarterly Journal of Economics_ 106, 709-738

> Diamond, D., 1993, Seniority and maturity of debt contracts _, Journal of Financial Economics_ 33, 348-368

Diamond, D. and R. Rajan, 2000, Banks, short term debt and financial crises: theory, policy implications and applications, _NBER Working Paper_ 7764

- Djankov, S., C. McLiesh, and A. Shleifer, 2006, Private credit in 129 countries, _Journal of Financial Economics_ , forthcoming

Duffie, D. and K. Singleton, 2003, Credit risks _,_ Princeton University Press Eichengreen, B., R. Hausmann and U. Panizza, 2003, Currency mismatches, debt intolerance and original sin, _NBER Working Paper 10036_

- Estrella, A., 2000, Credit ratings and complementary sources of credit quality information, _Basel Committee on Banking Supervision Working Paper_ , 3

Fan, J., S. Titman and G. Twite, 2006, An international comparison of capital structure and debt maturity, _HKUST Working Paper_

- Flannery, M., 1986, Asymmetric information and risky debt maturity choice, _Journal of Finance_ 41, 19-37

Galindo, A. and M. Miller, Can Credit Registries Reduce Credit Constraints? Empirical Evidence on the Role of Credit Registries in Firm Investment Decisions, Working Paper, Inter-American Development Bank

- Giannetti, M., 2003, Do better institutions mitigate agency problems? Evidence from corporate finance choices, _Journal of Financial and Quantitative Analysis_ 38, 185-212

- Guedes, J. and T. Opler, 1996, The determinants of the maturity of corporate debt issues, _Journal of Finance_ 51, 1809-1833

Harrison, M. and D. Kreps, 1979, Martingales and arbitrage in multiperiod security markets, _Journal of Economic Theory_ 20, 381-408

- Hart, O. and J. Tirole, 1988, Contract renegotiations and Coasian dynamics, _Review of Economic Studies_ 55, 509-540

26
|(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|
|VARIABLES|Weig|ht-for-age z-sc|ores||
|(0.090)|(0.089)|(0.091)|(0.091)|(0.091)|
|Completed O-levels<br>0.152|0.123|0.164|0.137|0.151|
|(0.148)|(0.149)|(0.148)|(0.149)|(0.149)|
|Completed A-levels<br>0.423|0.432|0.442|0.423|0.430|
|(0.290)|(0.285)|(0.289)|(0.288)|(0.287)|
|Technical college/University<br>0.577**|0.545**|0.598***|0.554**|0.587**|
|(0.226)|(0.227)|(0.229)|(0.230)|(0.229)|
|Private connection to pipeline<br>0.164|0.140|0.175|0.145|0.176|
|(0.192)|(0.191)|(0.192)|(0.192)|(0.192)|
|_Toilet Facility : Reference category - Flush toilet_|||||
|Latrine<br>-0.603***<br>|-0.601***|-0.619***|-0.548**|-0.637***|
|(0.225)|(0.223)|(0.224)|(0.226)|(0.224)|
|No toilet<br>-0.552**|-0.540**|-0.575**|-0.490**|-0.585**|
|(0.246)|(0.245)|(0.246)|(0.248)|(0.246)|
|Ethnic Minority<br>-0.155**|-0.151**|-0.159**|-0.155**|-0.157**|
|(0.065)|(0.064)|(0.065)|(0.064)|(0.065)|
|_Asset index: Reference category - poorest_|||||
|Asset index 2<br>0.114|0.091|0.128*|0.105|0.121*|
|(0.072)|(0.073)|(0.073)|(0.073)|(0.073)|
|Asset index 3<br>0.063|0.022|0.091|0.042|0.077|
|(0.081)|(0.082)|(0.082)|(0.083)|(0.080)|
|Rural<br>-0.272***<br>|-0.280***|-0.291***|-0.264***|-0.289***|
|(0.084)|(0.083)|(0.085)|(0.085)|(0.084)|
|Kampala<br>-0.217|-0.223|-0.183|-0.255|-0.200|
|(0.161)|(0.160)|(0.164)|(0.164)|(0.160)|
|Central without Kampala<br>-0.043|-0.028|-0.015|-0.047|-0.028|
|(0.088)|(0.088)|(0.091)|(0.088)|(0.087)|
|Eastern<br>-0.072|-0.063|-0.031|-0.067|-0.047|
|(0.089)|(0.086)|(0.094)|(0.085)|(0.085)|
|Northern<br>-0.179*|-0.132|-0.127|-0.127|-0.139|
|(0.092)|(0.085)|(0.088)|(0.085)|(0.085)|
|<br>Constant<br>0.271|<br>0.327|<br>0.249|<br>0.161|<br>0.276|
|(0.309)|(0.307)|(0.313)|(0.312)|(0.309)|
|Observations<br>1,908|1,906|1,908|1,908|1,908|
|R-squared<br>0.055|0.058|0.054|0.056|0.054|

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.

112
_Table 2: Plot Distribution Based on the Euclidean Distance from Household_

|||**Malawi (IHS3)**|||**Ethiopia (ESS2**|**)**|
|---|---|---|---|---|---|---|
|**Distance**|||**Cumulative**|||**Cumulative**|
|<br>**Interval**|**Frequency**|**Percentage**|<br>**Percentage**|**Frequency**|**Percentage**|<br>**Percentage**|
|[0.0, 0.5 Km)|9,798|53.67|53.67|12,282|61.51|61.51|
|[0.5, 1.0 Km)|3,363|18.42|72.09|3,070|15.38|76.89|
|[1.0, 2.0 Km)|2,888|15.82|87.91|2,455|12.30|89.19|
|[2.0, 3.0 Km)|755|4.14|92.05|862|4.32|93.50|
|[3.0, 5.0 Km)|404|2.21|94.26|537|2.69|96.19|
|[5.0, 10.0 Km)|306|1.68|95.94|342|1.71|97.91|
|[10.0,~ Km)|742|4.06|100.00|418|2.09|100.00|
|Total|18,256|100.00||19,966|100.00||

9
**Table 4:** Being economically active (any form of employment).

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|IDP|0.079***||0.077***|-0.010|
||(0.005)||(0.006)|(0.679)|
|Female||-0.239***|-0.238***|-0.347***|
|||(0.000)|(0.000)|(0.000)|
|IDP x Female||||0.173***<br>(0.000)|
|Age|Yes|Yes|Yes|Yes|
|HH size|Yes|Yes|Yes|Yes|
|N|10641|10641|10641|10641|
|_R_<sup>2</sup>|0.037|0.089|0.094|0.101|

Note: * p < 0.1, ** p < 0.05, *** p < 0.01. HC2 standard errors in parentheses.

23
**Table 9: Infrastructure Costs**

||**Hutto**|**n & Haller (20**<br>**Per Person**|**04)**|**C**|**hosen Cost an**<br>**Per hou**|**d Time Le**<br>**sehold**|**vels**|**(8)**|
|---|---|---|---|---|---|---|---|---|
||**(1)**|**(2)**|**(3)**<br>|**(4)**|**(5)**|**(6)**<br>|**(7)**|**Costs per**|
||**Invest.**<br>**($)**|**Yearly**<br>**Maint. ($)**|**Life**<br>**Time**<br>|**Invest.**<br>**($)**|**Yearly**<br>**Maint. ($)**|**Life**<br>**Time**<br>|**Discount**<br>**Rate**|**HH over**<br>**life time**|
||||**(years)**|**Sub-Sah**|**aran Africa**|**(years)**|||
|Basic san|39-57|4.88-6.21|10-30|399|43|10|3%|781|
|Basic wat|21-31|1.55-2.4|10-30|161|17|10|3%|309|
|Flush|120|4.84-10.03|30-50|840|70|25|3%|2099|
|Piped|102|8.34-12.75|30-50|714<br>|89<br>**Asia**|25|3%|2315|
|Basic san|26-50|3.92-5.70|10-30|300|34|10|3%|600|
|Basic wat|22-64|1.63-4.95|10-30|102|30|10|3%|363|
|Flush|154|5.28-11.95|30-50|924|72|25|3%|2210|
|Piped|92|5.97-9.95|30-50|552|60|25|3%|1623|
|<br>||||**Latin**<br>|**-America**<br>||||
|Basic san|52-60|6.44-12.39|10-30|312|74|10|3%|965|
|Basic wat|41-55|3.17-4.07|10-30|330|24|10|3%|545|
|Flush|160|6.46-13.38|30-50|960|80|25|3%|2400|
|Piped|144|9.06-15.29|30-50|864|92|25|3%|2509|

_Notes:_ Per person investment, operational costs per year and suggested operations times are taken from Hutton and Haller (2004) and WHO/UNICEF (2000). Cost estimates were converted to net present values costs per household based on a 3 percent discount rate and average regional household size.

We base our regional cost estimates for water and sanitation infrastructure on information provided by several recently published papers (WHO/UNICEF, 2000; Hutton and Haller, 2004; Clasen et al., 2007). Since we want to provide an estimate under the most conservative assumptions, we select the highest suggested initial investment cost as well as the highest suggested maintenance costs, and also take the lower end for the durability estimates as the basis for our calculation. As shown in the last column of Table 9, this implies region-specific cost estimates of around US$ 300 per household for basic improved water infrastructure, and US$ 800 for latrines over a life time of 10 years. We assume costs of US$ 2100-2400 and US$ 1600-2500 per household for flush toilets and privately piped water, respectively, with a durability of 25 years (Table 9, last column).

The main results of our cost-benefit analysis are displayed in Table 10. In columns (1) and (2) we show the most recent numbers available for income per capita and the total number of households for each of the 38 countries in our sample. In columns (3) and (4), we convert the country and scenario specific mortality improvements displayed in Table 6 into discounted number of life-years saved over the infrastructure time. Columns (5) and (6) are obtained by dividing the total estimated cost of necessary water and sanitation upgrades by the total number of life-years saved. Last, in columns (7) and (8) we show costs per life-year saved relative to each country’s income per capita.

25