rafmacalaba/datause-encoder-data huggingface dataset:
interesting alternative dimension to be explored in our empirical section. Third, FTS is not restricted to developing countries, so that the recipient pool covers a much broader spectrum of socioeconomic backgrounds. One potentially important shortcoming of FTS data is that donors’ reporting to the OCHA system is on a voluntary basis. To evaluate the magnitude of potential under-reporting, we compare the FTS data used in this paper with DAC data in Figure 1 below. While the DAC numbers are significantly higher than the numbers from the FTS on aggregate, differences are only minor once we exclude complex emergencies.<sup>12</sup>

# [Figure 1: FTS and DAC Data on Emergency Aid]

We complete the data set with socioeconomic information on recipient countries from the World Development Indicators (World Bank, 2006) and distance data from Gleditsch and Ward (2001). As proxy for the political ties between donors and recipient countries, we use the Gartzke index of similarity in states’ voting patterns in the United Nations General Assembly (Gartzke, 2002). Complete summary statistics and a detailed description of the variables used are provided in Table A.1 in the Appendix.

# **3.2 Data Description**

Total aid granted by the international community for the 491 emergencies in our sample amounts to US$ 3.06 billion dollars<sup>13</sup> . Total aid includes bilateral and multilateral aid, as well as donations from private sources. In Figure 2, we show a break down of total aid by state or institution, and rank donors in terms of the total amount granted and in terms of the number of emergencies assisted. The USA is the leading donor both in terms of the number of interventions and total aid provided, whereas the UK is second in terms of total aid provided, and Japan is second in terms of the percentage of emergencies assisted.

# [Figure 2: Major Donor Countries and Institutions]

As shown in Tables 1a and 1b, the degree of coordination within the international community is rather small. The correlation of aid interventions is strictly below 0.5 (Table 1a) whereas the correlation of the actual amount given (Table 1b) ranges from 0.59 between Germany and Japan to only 0.18 between Norway and the United States. In Figure 3, we summarize total contributions by donor and year. Total contributions vary significantly across years, and do not show a clear time trend for any donor. The aggregate data show little evidence of fixed annual budgets, and the correlation between total expenditure per country and the number of calamities appears fairly low. Another important source of variation in our data set is the geographic distribution of disasters. On aggregate, Asia has the largest number of disasters, with South and South-East Asian countries accounting for 73% of disasters over the entire period. Of the 111 recipient countries in our sample, Indonesia is the most exposed one, with 25 natural disasters, followed by India (18), and the Philippines (16). Floods are the most frequent natural disaster type, representing 49% of the sample, followed by wind storms (21%) and earthquakes (15%).

6
|Title|Author|Date|Contact|
|---|---|---|---|
|WPS13Objectives and Methods of a World||||
|Health Survey|Trudy Harpham<br>Ian Timaeus|June1988|A. Menciano<br>33612|
|WPS14The Optimal Currency Composition<br>of||||
|External Debt|StlJn Claessens|June1988|S.Berteismeler<br>33768|
|WPS15 Stimulating<br>Agricultural<br>Growth and<br>Rural Development In Sub-Saharan||||
|Africa|Vijay S. Vyas|June1988|H. Vallanasco|
||Dennis Casley||37591|
|WPS16Antidumping<br>Laws and Developing||||
|Countries|Patrick Messerlin|June1988|S.Torrijos<br>33709|
|WPS17Economic Development<br>and the Debt<br>Crisis|Stanley Fischer|June1988|C.Papik<br>33396|
|WPS18China's Vocationa:<br>and Technical<br>Training|Harold Noah<br>John Middleton|June1988|W.Ketema<br>33651|
|WPS19 Cote d'lIvoire's<br>Vocational and<br>Technical Educetion|Christiaan<br>Grootaert|<br>June1988|R.Vartanian<br>34678|
|WPS20Imports and Growth in Africa|Ramon Lopez<br>VInod Thomas|June1988|61679|
|WPS21Effects of European VERs on Japanese<br>Autos|Jaime de Melo<br>Patrick Messerlin|June1988|S.Fallon<br>61680|
|WPS22Methodological<br>Problems in Cross-<br>Count ,y Analyses of Economic Growth|Jean-Paul<br>Azam<br>Sylviane Guillaumont|June1988<br>|E. Zamora<br>33706|
|WPS23Cost-Effective<br>Integration<br>of<br>Immunization<br>and Basic Health Services<br>in Developing<br>Countries: The Problem<br>of Joint Costs|A. Mead Over, Jr.|||
|WPS24Review of World Bank Investments<br>In<br>Vocational<br>Education and Training<br>for Industry|John Middleton<br>Terri Demsky|||
Figure 1). The failure of MPTC's corporatization to improve telephone access in Malawi is consistent with the observation that performance contracts and other reforms designed to improve the functioning of weak state-owned enterprises rarely succeed in developing<sup>countries</sup> (Shirley and Xu, 1998, 2001; World Bank, 1995).

<!-- Start of picture text --> 35.0<br>30.0<br>25.0<br>20.0 -<br>15.0/<br>10.0.<br>5.0 -<br>0 - .<br>_ _ _ _ _ _ _ _<br><!-- End of picture text --> Figure 3: Waiting Time for Telephone Connection (In Years) **Source: International Telecommunication Union. (2001) Note: Waiting times are calculated by dividing the waidist by the average main lines growth over the previous three yeas.** The low service penetration was not due to lack of demand - MPTC consistently had long waitlists. By 1997, it would have taken MPTC about 25 years to clear its waiting list at the rate of expansion that it was managing at that time (see Figure 3). In practice, since many people do not bother to put their names on a waiting list when there is an extremely low chance of actually getting a phone, actual demand was probably considerably higher than the waiting list suggests. For example, Pyramid Research<sup>estimatedthat</sup> total demand in Malawi was around 500,000 lines in 1997 (Economist Intelligence<sup>Unit,1999b)</sup> - compared to only 36,574 operational lines.

10
(though both effects are stronger for men). Having more male adults in the family decreases the probability of women entering casual labor.

One concern about our model of participation in the casual labor market is that it may not be adequately capturing the household income effect on individual participation. This could be particularly important for women’s choice about whether to supply casual labor. Another concern is that it may not sufficiently control for characteristics that explain why an individual’s usual activity status during the year was unemployment rather than casual labor. To address these concerns we also estimated an augmented version in which we added household consumption expenditure per person and also a dummy variable for whether the usual status was unemployment. Both were statistically significant with the expected signs, though there are clearly concerns about the likely endogeneity of both variables. We will refer to this as the augmented specification and test the sensitivity of our main results to this specification.

- _4.1 Incidence of the gains from a guaranteed minimum wage_

The incidence of the direct income gains from the program across quintiles of consumption expenditure per capita can be found in Table 4. Figures 1 and 2 plot the absolute and proportionate gains (respectively) against the rank in terms of consumption expenditure per person. Figure 3 gives the impact on the cumulative distribution function (indicating the reduction in poverty for a wide range of possible poverty lines). (Note that first-order dominance is automatic under our assumptions.) The absolute mean gain from the EGS tends to fall as household consumption per person rises (Figure 1). At an EGS wage rate of Rs 40 per day, we find that the gain represents 27% of the consumption of the poorest 20%, falling to 3% for the richest 20% (Table 4, top panel). At the wage rate of Rs 50, the gain is 47% of consumption for the poorest quintile, falling to 6% for 15
- “Human Capital and Regional Development,” _Quarterly Journal of Economics_ , 128, no. 1: 105-164 (2012).

- HOLMÉN, MARTIN, AND PETER HÖGFELDT, “A law and finance analysis of initial public offerings”, _Journal of Financial Intermediation_ 13 (3): 324-358 (2004).

- HOPENHAYN, HUGO, “Entry, Exit, and Firm Dynamics in Long Run Equilibrium,” _Econometrica_ , 60, no. 5 (1992), 1127-1150.

- HSIEH, CHANG-TAI, AND PETER KLENOW, “Misallocation and Manufacturing TFP in China and India,” _The Quarterly Journal of Economics_ , 124 (2009), 1403–1448.

- KNACK, STEPHEN, AND PHILIP KEEFER, “Does Social Capital Have an Economic Payoff? A CrossCountry Investigation,” _The Quarterly Journal of Economics_ , 112, no. 4 (1997), 1251-1288.

- KNACK, STEPHEN, AND PAUL ZAK, “Trust and Growth,” _The Economic Journal_ , 111 (2001), 295-321.

- KHANNA, TARUN, AND KRISHNA PALEPU, “Emerging Market Business Groups, Foreign Intermediaries, and Corporate Governance”, National Bureau of Economic Research 265 - 294 (2000).

- LA PORTA, RAFAEL, FLORENCIO LOPEZ-DE-SILANES, ANDREI SHLEIFER, AND ROBERT VISHNY, “Trust in Large Organizations,” American Economic Review, 87, no. 2 (1997), 333-338.

- LA PORTA, RAFAEL, FLORENCIO LOPEZ-DE-SILANES AND ANDREI SHLEIFER, “Corporate Ownership Around the World,” Journal of Finance, 54, no. 2 (1999), 471-518.

- LEMOS, RENATA, AND DANIELA SCUR, “All in the Family? CEO Choice and Firm Organization,” Working Paper, University of Oxford, 2018.

- LEVCHENKO, ANDREI, “Institutional Quality and International Trade,” Econometrica, 71, no. 6 (2007), 1695-1725.

- LINS, KARL, “Equity Ownership and Firm Value in Emerging Markets”, _Journal of Financial and Quantitative Analysis_ 38 (1): 159-184 (2003).

- LUCAS, ROBERT, “On the Size Distribution of Business Firms,” Bell Journal of Economics, 9 (1978), 1508–523.

- MALONEY, WILLIAM, AND MAURICIO SARRIAS “Convergence to the Managerial Frontier,” World Bank Policy Research Working Paper No. 6822, 2016.

- MELITZ, MARC, “The Impact of Trade on Intra-Industry Reallocations and Aggregate Industry Productivity,” Review of Economic Studies, 74, no.1 (2003), 791-819.

- MORCK, RANDAL, DAVID STRANGELAND, AND BERNARD YEUNG, “Inherited Wealth, Corporate Control, and Economic Growth: The Canadian Disease?” In _Concentrated Corporate Ownership_ , Nber Conference Volume, (Chicago University Press, Chicago, 2000).

- PÉREZ-GONZÁLEZ, FRANCISCO, “Inherited Control and Firm Performance,” American Economic Review, 96, no.5 (2006), 1559-1588.

- RAUCH, JAMES, “Networks versus Markets in International Trade,” Journal of International Economics, 48,

25
# **Table 10: Nonlinear Results with Productive and Non-productive Expenditures (Dynamic Panel - GMM)**

## **_Dependent variable: Growth rate of GDP per capita_**

||Fast growing<br>countries|Comparison<br>group|Whole sample<br>pooled|Whole sample<br>with dummies|
|---|---|---|---|---|
|Openness|0.024|-0.197|0.056|0.014|
|(% of GDP)|(0.734)|(-0.96)|(1.026)|(0.118)|
|Total government revenue|-0.665|0.655|0.050|0.017|
|(% of GDP)|(-2.164)**|(1.102)|(0.113)|(0.03)|
|Productive expenditure (-1)|6.061|0.659|1.06|...|
|(% of GDP)|(1.687)*|(0.456)|(1.037)||
|Square term of Productive expenditure (-1)|-12.969|0.354|-0.687|...|
|(% of GDP)|(-1.508)|(0.046)|(-0.187)||
|DFAST*Productive expenditure (-1)|...|...|...|4.016|
|(% of GDP)||||(0.457)|
|DFAST*Square term of Productive expenditure (-1)|...|...|...|-8.252|
|(% of GDP)||||(-0.426)|
|DCOMP*Productive expenditure (-1)|...|...|...|0.209|
|(% of GDP)||||(0.089)|
|DCOMP*Square term of Productive expenditure (-1)|...|...|...|3.393|
|(% of GDP)||||(0.212)|
|Non-productive expenditure (-1)|-2.125|-1.179|-1.377|-1.440|
|(% of GDP)|(-2.5)**|(-1.608)|(-2.06)**|(-2.031)**|
|Budget surplus|0.735|-0.225|-0.009|0.073|
|(% of GDP)|(1.58)|(-0.321)|(-0.024)|(0.114)|
|Inflation - consumer price index|-0.214<br>(-1.816)*|-0.089<br>(-3.245)***|-0.08<br>(-4.407)***|-0.088<br>(-1.866)*|
|Growth rate of GDP per capita (-1)|-0.306|-0.387|-0.393|-0.355|
||(-1.487)|(-2.328)**|(-2.564)**|(-1.553)|
|No. of observations|99|171|270|270|
|J-test|1.007|2.321|2.511|2.919|

Note: The estimation method is a dynamic GMM. Annual data are used. (-1) indicates variables lagged one period. DFAST is the dummy variable which is 1 for fast growing countries and 0 otherwise. DCOMP is the dummy variable which is 1 for the comparison group and 0 otherwise. t-statistics are given in parenthesis. * indicates 10% significance level, ** indicates 5% significance level, and *** indicates 1% significance level. These significance levels are equal to one minus the probability of rejecting the null hypothesis of zero coefficients. J-test is for overidentification problem where H0: there is no overidentification problem. We fail to reject in each case.

41
theory, skills shortages would be revealed by a high wage premium for scientists and engineers although analysis to date has only identified the general rising premium to tertiary education found globally. However, surveys of private firms suggest, for example, that Chile ranks globally very low on collaboration of the private and university sectors.<sup>14</sup> Though most major universities have offices to promote linkages, only the Universidad de Concepción has any incentives for faculty to collaborate with the private sector in promotion criteria.<sup>15</sup>

# **5. Conclusion**

Countries do have innovation shortfalls, but we have argued that their diagnosis requires more than simple unconditional comparisons of R&D or other related indicators. Standard issues of comparative advantage influence the optimal level of knowledge accumulation and generation. Further, even if we establish conditionally low levels of innovation, it is not immediately clear whether the problem pertains particularly to this factor, or whether there are barriers to accumulation more generally that need to be addressed. We offer approaches to both issues and illustrate their application for Chile, a country which is currently thinking seriously about improving its innovation policy. The results that emerge suggest that this country does indeed suffer from a true innovation shortfall, and we offer some tentative ideas on what may be causing it. Clearly, we don’t have the last word on the issue and we encourage further refinements both in technique and data.

> 14 World Economic Forum (various).  Only 12% of Chilean firms have signed agreements with universities compared to for instance, 40% in Finland (de Ferranti et al 2003). 15 Mullin (2005)

28
10 will confine ourselves for the remaining of this section to the analysis of comparisons within SSA. It is clear that EIAL and OAL have pursued rnore expansive macroeconomic policies than their NAL counterparts , with the fiscal deficit ratios to GDP averaging 6.6%, 3.6%, and 2.4%, respectively. Not surprisingly the rate of domestic inflation averaged 14.9% and 14.8% respectively for the first two gruups, compared to 10.9% for NAL countries. Also the first two groups have been less conservative compared to the last one in terms of external debt policies. The stock of external debt as a ratio to GDP averaged 33.1% for EIAL, and 26.3% for OAL compared to 23.5% for NAL. The debt service ratios to export on the other hand, averaged 7.7% and 5.5% for the first and second group and only 3.8% for the NAL countries.

The external debt story is reflected on the comparators performances in terms of their resource balances. Over the period under consideration, domestic absorption ratio to GDP (the negative of the resource balance ratio) for the three groups averaged 10.6%, 13.6%, and 10.1%, respectively. Also over this initial 1970s period, the above "would be" adjusting two groups of countries did not adopt more export-oriented policies or achieve better export performance compared to the other group. While the real exchange rate index for the three groups ranged between 93 and 98, export GDP ratio averaged 30.2% for EIAL and NAL compared to only 21.0% for OAL. These comparisons provide a caue against the relatively more expansive external debt policies adopted by the EIAL and OAL in the period prior to reform.

Perhaps the most significant aspect of the initial conditions that set NAL countries from the other two groups is the record of growth and the implied productivity of investment. While the NAL countries managed to achieve an annual average rate of growth of 6.0% over the 19709 decade, the EIAL and OAL grew by
if a larger share of their coworkers is eligible for paternity leave. This suggests that paternity leave may negatively affect fathers’ earnings by causing them to lose out on high-wage positions to competing coworkers who do not take leave.

It is worth noting that much of the evidence on family leave policies is based on data from high-income economies. However, a small number of papers use data from developing economies; given their importance in a global study of the evolution of leave polices, we highlight them here. A study of maternity leave policies in 121 low- and middle-income economies by Fallon, Mazar and Swiss (2017) finds no evidence of a positive impact on female labor supply; however, the authors find a positive association with a range of development outcomes, including reduced infant and child mortality. Using firm-level data from 66 mostly developing economies, Amin and Islam (2019) find a positive association between maternity leave provisions and female labor supply at the firm level. They highlight that the results are much stronger in countries where maternity benefits are entirely funded by the government. Similar conclusions are reached by the authors in an update to their previous analysis that extends the country coverage to 111 countries and looks at maternity leave policies in greater depth (Amin and Islam, 2022). Again, looking specifically at the relationship between paid maternity leave and female employment in the private sector, the authors find a large and significant positive correlation between the length of maternity leave and the share of female workers in a firm. The authors confirm their previous finding that context matters, as the positive relationship is much stronger when the maternity benefits are paid for by the government, and where the share of the female population at childbearing age is larger.

The only paper identified in this research that considered the impacts of paternity leave policies in developing economies is by Amin, Islam and Sakhonchik (2016). Using data from 53 developing economies, the authors find a strong positive association between the provision of paternity leave and female employment at the firm level.

We contribute to this body of literature in a number of ways. Firstly, our data set in this analysis covers 190 countries over 52 years, and captures leave granted to both parents; this allows us to provide what is, to the best of our knowledge, a novel overview of the global trends in family leave policies over five decades. Secondly, the global nature of our data allows us to consider the relationship between leave policies on women’s labor market outcomes across regions. Finally, while earlier studies have tended to focus on either leave granted to mothers or to fathers, we assess both types of leave by focusing on the gap between the leave allocated to mothers and fathers.
race-specific unit cost show that the poorest quintile got about 14 percent of the subsidy compared with 35 percent for the richest.

There are _costs_ associated with the use of public services, even for services that are provided free of charge to the household. Some of these are transaction costs to the extent that they must be incurred in order to gain access to the service. These include mainly transportation and the opportunity cost of the time use to get the service (Demery 2000). In addition, one should consider household spending that enhances the benefits obtainable from the publicly provided service. In the case of education, these expenditures would cover such things as books, uniforms, and other school supplies. The total cost of access and use can represent a significant burden<sup>27</sup> for low income households and limit their use of the service. In education such costs have been found to explain non-enrollment or drop-outs. A recent evaluation of the welfare impact of rural electrification by the Independent Evaluation Group (IEG) of the World Bank found that even in villages that have been connected to a national grid for 15 to 20 years, one can still find 20 to 25 percent of households unconnected because they cannot afford the connection fee. A major implication of this state of affairs is that tariff structures designed to be progressive end up being regressive subsidy schemes (World Bank 2008).

Finally, we note that benefit incidence results may be sensitive to the choice of the _welfare measure_ . As noted earlier, accounting for need differences across income levels can reveal more inequality than standard benefit incidence analysis would. Demery (2000) explains that such demographic differences across quintile are partly due to the use of per capita total expenditure as the welfare indicator. Such differences may indeed be attenuated or disappear all together if one were to assign individuals to quintiles on the basis of per adult equivalent expenditure. To demonstrate this point, the author cites a benefit incidence study of public education in Ghana (1992). When the population is ranked on the basis of per capita expenditure, it is found that the poorest quintile gets about 22 percent compared with 17 percent when per adult equivalent expenditure is used as the welfare indicator. In contrast, the share of the richest quintile increases from 14 percent to about 18 percent.

> 27 The extent of this burden can be assessed on the basis of the affordability ration.  In the case of health this ratio compares household spending per visit with its per capita non-food expenditure (Demery 2003).

32