rafmacalaba/datause-encoder-data huggingface dataset:
16 households in Guatemala spend more at the margin on investment goods, specifically, housing and education. At the margin, Table 6 shows that households receiving international remittances spend 2 percent more on housing and 58 percent more on education than do households with no remittances. When disaggregated by level of education, most of these increments to expenditure on education go into secondary school education. At the margin, households receiving international remittances spend 142 percent more on secondary education than do households with no remittances. The paper observes that such increased expenditure on secondary school education by remittancereceiving households can help raise the level of human capital in Guatemala, thereby boosting the rate of overall economic growth.

# 5.  Summary and Areas for Future Work

This paper has used a new data set of 115 developing countries and the results of recent household-level studies from 6 developing countries to analyze the impact of official international remittances on the developing world. Five key findings, and two areas for future work, emerge.

First, with respect to the question of which countries receive international remittances, the study shows that two geographical regions dominate: Latin America and the Caribbean, and South Asia. In 2003 these two regions of the developing world received over 65 percent of all official international remittances. By contrast, in that year Sub-Saharan Africa received less than 5 percent of all official international remittances.

The second finding is closely linked to the first. The econometric model developed in this paper shows that two variables – distance and level of country income (per capita GDP) – are the most significant economic factors explaining the receipt of official international remittances. With all other things held constant, countries located closer to a major remittance-sending region -- United States, OECD- Europe, or the Arab Gulf – are more likely to receive more per capita remittances. At the same time, middleincome developing countries – those with annual per capita GDP between $736 and $2,935 -- receive more per capita international remittances, because their citizens possess both the incentive to go work abroad and the ability to afford the travel costs associated with international migration. The combination of these two factors help to explain why
**Table 2. Expenditures in Education per Student (Fees/tuition/unforeseen expenses)"' by Level**

|||**of Education, 1996**|||
|---|---|---|---|---|
|**Poverty Status**|**Primary**|**Lower Secondary**|**Upper Secondary**|**Tertiary**|
|**Public and Private sc**|**hools**||||
|Extreme|76.7|268.2|851.9|1828.7|
|Moderate|186.3|491.6|975.9|835.9|
|Non poor|1378.9|1404.7|2965.1|5448.7|
|Total|425.4|750.1|1996.2|4466.8|
|**Public schools**|||||
|Extreme|74.6|262.4|760.1|1828.7|
|Moderate|179.4|485.2|883.7|817.4|
|Non poor|307.4|712.5|1292.1|2577.7|
|Total|156.8|492.9|1057.4|2141.6|
|**Private schools**|||||
|Extreme|1422.5|1252.5|2845.0|0.0|
|Moderate|1739.0|1088.7|2540.3|1179.4|
|Non poor|6468.1|6539.0|8515.2|12950.5|
|Total|6241.9|5915.4|7495.3|12451.3|

_Source:_ ENIGH 96 1/ Annual pesos per student The total cost (student expenditure plus government subsidy) per student in primary public school corresponds to about 35% of the private primary school cost. For students in lower and upper secondary it represents 43% and 53%, respectively. On the other hand, the cost of tertiary level is 13% higher in public schools as compared to private (see tables below). An interesting question that arises is why the cost at tertiary level is higher in public than in private schools. Is it because the subsidy is not being used efficiently, or because the infrastructure (research institutes, libraries, museums, entertainment centers, etc.) they offer is costly?

In the next section a technique is applied that will allow us to evaluate the impact of public expenditures on household spending patterns.

**Table 3. Individual Educational Expenditures"** plus Subsidy in Public Schools by Poverty Status<sup>2</sup> '

|**Poverty Status**|**Primary**|**Lower Secondary**|**Upper Secondary**|**Tertiary**|
|---|---|---|---|---|
|Extreme|2799|3266|5002|16970|
|Moderate|3267|3852|5489|16322|
|Non poor|3941|4626|6444|18629|
|Total|3268|3883|5686|17670|

_Source:_ ENIGH 96 and DGPPyP, SEP " Fees/tuition/unforeseen expenses, services and materials, 2/ Annual pesos

**Table 4. Individual Educational Expenditures'/ in Private Schools by Poverty Status**

|**Poverty Status**|**Primary**|**Lower Secondary**|**Upper Secondary**|**Tertiary**|
|---|---|---|---|---|
|Extreme|2295|2125|3717||
|Moderate|2390|1740|3191|1831|
|Non poor|9851|9922|11898|16334|
|Total|9387|9060|10640|15596|

_Source:_ ENIGH 96 and DGPPyP, SEP 1/ Fees/tuition/unforeseen expenses, services and materials, 2/Annual pesos 4
# 1. INTRODUCTION

Empirically, traditional money demand equations are frequently characterized by periods of "missing money", unstable parameters, and autocorrelated errors. The common practice to solve these problems consists in changing the specification of the regressions once the shifts are identified. These shifts are usually associated to financial innovation<sup>1</sup> • To solve the estimation problems, it is common to find the inclusion of dummy variables, lagged variables, proxies for expectations, etc. Often, these amendments improve the fit of the models, but provide no guarantee that the estimated equation is the true long-run relationship. In other words, spurious inclusion of variables may result in biased estimates of the interest rate and income elasticities of the money demand.

In this paper we provide an alternative approach to deal with the unobservable process of financial innovation. It consists in modelling financial innovation as shocks that have permanent effects on the money demand, analogous to productivity shocks in production functions. The entire path of financial innovation is estimated simultaneously with the other parameters, using data for Chile (1975-89) and Mexico (1980-89), by applying a procedure due to Cooley and Prescott (1973a,b,1976)<sup>2</sup> .

Our definition of financial innovation is very broad. It involves pure

> 1 Discussions of instability of the demand for money in the U.S. can be found in Goldfeld (1976) and Friedman (1988). A comprehensive survey on the state of the art of money demand equations in developed countries can be found in Goldfeld and Sichel (1990). For developing countries see Fasano-Filho (1986), Marquez (1987), Melnick (1989), Viren (1989) and Laban (1990).

> 2 In developing countries, not only "pure financial innovation", but volatility in rates of inflation and currency substitution (or "dollarization") have been also invoked as provoking shifts in money demand relationships. They will be included in our definition of financial innovation as long as they have permanent effects on money demand equations.

1
59 Today, _unemployment insurance_ in China, initiated in 1986 and revised in 1999, covers about 105 million urban individuals (in 2004).<sup>117</sup> The maximum duration is high by international comparisons, between 12 and 24 months (depending on how long premiums have been paid for a particular individual). The replacement rate (the ratio of the benefit to previous wage) is fairly generous for many “urban insiders” – both compared to income security for workers in many other developing countries and (of course) to the income level of unemployed workers not covered by the system. The OECD (2002, pp. 566-567) reports a replacement rate of about 50 percent for a large fraction of those insured, although there are also reports of lower levels (about 30 percent) for others.<sup>118</sup> Presumably, the rationale for this relative generosity towards some urban workers is to create an acceptable substitute for the receding job guarantees by state-owned enterprises. The system may, however, run into financing problems in the future, since structural unemployment in China is likely to be high during coming decades.<sup>119</sup> A financially and socially safer approach might have been if China, at its present stage of economic development, had chosen a less generous system for the most favored groups, and instead tried to cover a larger share of the labor force. Since unemployment insurance is difficult to extend to the farm population, for which unemployment is even difficult to define, improved crop-failure legislation, and/or improved natural-disaster relief, might be substitutes for unemployment insurance for this population.

There is also a “bottom level” safety net in urban areas in the form of means-tested _social assistance,_ whose main component is an “urban living standard guarantee”,<sup>120</sup> with a corresponding, although much less generous, program in rural areas. Although the take-up rate for social assistance is rather low today, about a quarter of the number of eligible individuals (Social Policy Research Centre, 2002, p. 11), it may increase by receding stigmatization of living off benefits, in particular if unemployment reaches high levels for prolonged periods.

> 117 As in most developed countries today, the benefits are (or at least will be) financed by payroll taxes on firms (two-thirds of the cost) and employees (one-third).

> 118 The rules require that the benefit level is set between local so-called “minimum living standard” ( _dibao_ standard) and the minimum wage (or possibly a fraction of this). According to the OECD, the benefit level is usually 120-150 percent of the minimum-standard in the province in question.

> 119 The OECD (2005a) reports that 7.4 million people received unemployment benefits at the end of 2003. 120 The benefit level in this system is 25-30 percent of the average income in the district, or province, where the individual lives (Tang, 1999). Today this system provides income support for about 20 million people in urban areas, and about 5 million individuals in rural areas (OECD, 2005a, p. 85).
operating surplus term in an IO table) accruing to a firm type via direct and indirect exports, respectively. By “direct”, we refer to profits accruing to direct exporters. By “indirect”, we refer to profits accruing to firms that supply goods and services to downstream exporters, through the domestic input-output network. Column (1) in Panel A of Table 4 reports a total of 885 billion RMB profits (about 120 billion USD in 2007 exchange rate) accruing to direct exporters in 2007. Similar to our analysis of value added exports above, this value of profits for direct exporters may underestimate the actual export-induced profits in the domestic economy. Therefore, we also estimate profits accruing to firms that sell inputs and services, directly and indirectly, to exporters in the economy (defined in the same way in Table 2). When both direct and indirect exporters’ profits are included (column (2)), total export-related profits increased to 2.3 trillion RMB (about 315 billion USD). As reported in Panel B, direct export-related and total export-related profits for 2010 were 763 billion and 2.2 trillion RMB, respectively.<sup>14</sup> The decline in both profit measures, despite the fact that value added exports increased between the two years, suggests that the Chinese economy may have become more competitive over time.

How important are export activities in generating profits in the Chinese economy? According to the IO tables, total profits (capital income) of the Chinese economy were about 8 trillion RMB in 2007 and 9.7 trillion RMB in 2010. In other words, if we focus on profit accrued to direct exporters only (i.e., 885 and 763 billion RMB), exports generated about 11% and 8% of China’s total profits in 2007 and 2010, respectively. On the other hand, if we also include profit accrued to firms that also supply intermediate goods and services to exporters, profits that could be attributed to exports increased to about 29% in 2007 and 23% in 2010.

# (Insert Table 4 here)

Similar to the decomposition of value added exports conducted in Table 2, we can also distribute export-related profits to different firm types. As reported in column (3), we find that FIEs have the highest profit per worker derived from exports (both direct and indirect), while SMEs have the lowest export-related profit per worker. Specifically, profit per worker due to exports was 6140 RMB for FIEs in 2007, 1250 RMB for SOEs, 1720 RMB for LPs, and only 700 RMB for SMEs. Using 2008 firm census data, along with 2007 and 2010 IO tables, we find that export-related profit per worker declined from 1150 RMB in 2007 to 999 RMB in 2010 for the aggregate economy. Those for FIEs and LPs, however, increased to 6440 and 1980 RMB, respectively.

Column (4) reports each firm type’s share in total export-related profits. SMEs are responsible for 47% of

> 14 Notice that we are still using 2008 firm census to measure aggregate surplus and surplus by firm type.

24
TABLE 12: marginal effects of ordered logit, probit and 2SLS ordered probit regressions on multiple outcome of binary borrower performance

||Ologit<br>(1)|Ologit FE<br>(2)|Oprobit<br>(1)|Oprobit FE<br>(2)|Oprobit<br>2SLS(1)|
|---|---|---|---|---|---|
||Borrower|Borrower|Borrower|Borrower|Borrower|
|Outcome=1|-0.063***<br>(0.010)|-0.049***|-0.070***<br>(0.015)|-0.053***|-0.156***|
|Outcome =2|-0.417***<br>(0.022)|-0.423***|-0.411***<br>(0.021)|-0.423***|-0.528***|
|Outcome =3|-0.194***<br>(0.016)|-0.214***|-0.166***<br>(0.014)|-0.187***|-0.141***|
|Outcome =4|0.033*<br>(0.019)|0.027*|0.012<br>(0.017)|0.011|0.093***|
|Outcome =5|0.581***<br>(0.014)|0.608***|0.572***<br>(0.014)|0.602***|0.638***|
|Country FE||Yes||Yes|Yes|
|Year FE||Yes||Yes|Yes|

Note:<sup>+</sup> the marginal effects computed for the IV probit come from a numerical procedure, which requests that all specified variables and observations be retained in the maximization process. The results from this regression do not significantly change from the 2SLS probit, for which however we cannot compute the marginal effects.

29
<mark>Maternal Mental Health and Its Influence on Children’s Early Development: Evidence from Khyber Pakhtunkhwa, Pakistan</mark> Mahreen Tahir-Chowdhry<sup>*</sup> Elizabeth Hentschel*<sup>-</sup> Heather Tomlinson*<sup>-</sup> Amna Ansari* Amer Hasan* Aisha Yousafzai<sup>•</sup> Naveed Hussain*

**Keywords** : Early childhood development (ECD); Depression; Anxiety; Parenting stress; Fragile, Conflict and Violence-affected (FCV); refugees

**JEL Classification** : I14, I15, I24, I25

> * Education Global Practice, World Bank

> - <mark>Yale Child Study Center</mark>

- Harvard T.H. Chan School of Public Health
is the same as the share of imports from that country over total imports. Denoting, as above, _H_<sup>_rs_</sup> as the matrix of intermediate goods and services traded between region _r_ and regions _s_ , we can express the imports of region _s_ as: We can then calculate the elements of _H_<sup>_rs_</sup> and of _w_<sup>_rs_</sup> as Note, however, that CO2 emissions in GTAP are limited to those from fossil fuel consumption alone. Clearly, a fuller picture of virtual carbon would need to include emissions from other greenhouse gases and CO2 emissions from agriculture, land-use change and other processes. It is important also to understand how trade in energy goods (such as coal or crude oil) is treated in this analysis. In the IO approach, carbon is accounted for when it is emitted in a production process. This means that exports of crude oil, for example, are measured in terms of how much carbon was emitted in its drilling, pumping, transporting and processing but not in terms of how much carbon the oil contains. The latter is only measured when (and where) the oil is actually burned and the carbon released.

Finally, because the GTAP data are measured in dollars at market exchange rates, it is worth considering whether the (relatively) low price of non-tradables in developing countries could distort the analytical results<sup>6</sup> . Since the sectors with the highest carbon intensity are typically the big traded sectors (metals, minerals, petroleum, chemicals, cement, and pulp and paper) this would not appear to be a concern. Moreover, for highly carbon-intensive non-tradables, the low price of these goods (resulting from the use of market exchange rates) is fully offset by a correspondingly high emission coefficient. When we wish to employ values for GNI as a numeraire below, we use both PPP and market exchange rate values.

# **5. Theoretical, Legal and Ethical Considerations for Border Taxation**

As noted in the Introduction, our main interest in employing IO analysis to trace the flows of virtual carbon in international trade is to examine the potential size of border taxes on virtual carbon. It is important, therefore, to consider the theory of border taxation,

> 6 As noted in World Bank (2008), production in a developing economy will typically be underestimated if market exchange rates are used to compare its value with that in high-income economies. Because developing economies tend to have relatively lower wages leading to lower prices for non-traded goods and services, a unit of local currency has greater purchasing power within a developing economy than it does in the global market. It follows that conversion to an international currency (e.g. the US dollar) for the sake of comparison results in a distortion. PPPs adjust for differences in price levels between economies, which may not be reflected in market exchange rates, at least in the short run.

10
- 22 -

Table 4: Propomion of Less-Developt4 Countries Offering Instruction in Selected Subjects of the Primary School Curriculum by Predicted GNP Growth Rate and Gross Primary Enrollment Rate (PER)*

||Pos. GNP|Neg. GNP|Pos. GNP|Neg. GNP|
|---|---|---|---|---|
||High PER|High PER|Low PER|Low PER|
||(N=25)|(N=13)|(N=13)|(N=9)|
|Comb.Lang.|100.0|100.0|100.0|100.0|
|<br>Nat.Lang.|96.0|76.9|76.9|55.6|
|Loc.Lang.|4.0|38.5|15.4|0.0|
|For.Lang.|20.0|30.8|_15.4_|22.2|
|<br>Off.Lang.|28.0|46.2|38.5|77.8|
|Mathematics|100.0|100.0|100.0|100.0|
|Science|100.0|100.0|100.0|100.0|
|Comb.Social Sci.|100.0|100.0|100.0|100.0|
|Social Studies|72.0|76.0|61.5|44.5|
|History|32.0|38.5|46.2|55.6|
|<br>Geography|32.0|38.5|46.2|55.6|
|Civics|36.0|30.8|46.2|33.3|
|Comb.MoralIRel.|96.0|53.9|84.6|66.7|
|Religion|52.0|38.5|46.2|44.4|
|Moral Ed.|24.0|30.8|15.4|22.2|
|Hygiene|40.0|23.1|53.9|22.2|
|Aesthetic Ed.|92.0|92.3|100.0|100.0|
|Music|68.0|76.9|100.0|77.8|
|Art|92.0|84.6|100.0|100.0|
|Physical Ed.|92.0|92.3|100.0|100.0|
|Hygiene|40.0|23.1|53.9|22.2|
|Comb.Voc.Ed.|72.0|76.9|76.9|88.9|
|Manual Training|40.0|61.5|46.2|44.4|
|<br>Agriculture|28.0|23.1|30.8|44.4|
|<br>Domestic Science|24.0|15.4|46.2|55.6|
|Vocational Ed.|8.0|0.0|7.7|0.0|
|Business|4.0|0.0|0.0|0.0|
|Other|40.0|46.2|30.8|33.3|

*Key: Pos.GNP = Positive GNP Growth Rate; Neg.GNP = Negative GNP Growth Rate
# Labor Market Effects of Global Supply Chain Disruptions<sup>*</sup>

Mauricio Ulate Jose P. Vasquez Roman D. Zarate

**JEL codes:** F10, F11, F16, F40, F66.

**Keywords:** Supply Chain Disruptions, Trade Costs, Downward Nominal Wage Rigidity.

> *Mauricio Ulate: Federal Reserve Bank of San Francisco, Jose P. Vasquez: LSE and CEPR, Roman Zarate: Development Research Group, The World Bank. We thank Marco Badilla, Lorenzo Caliendo, Juanma CastroVincenzi, Isabela Manelici, Joan Monras, Ishan Nath, Andres Rodriguez-Clare, Nicholas Sander and the whole department at the FRBSF for their help and useful comments. Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent the views of the Federal Reserve Bank of San Francisco, the Federal Reserve System, or the World Bank.
Policy Research Working Paper 5486

# **Abstract**

This paper studies the effect of increased access to antiretroviral therapy on risky sexual behavior, using data collected in Mozambique in 2007 and 2008. The survey sampled both households of randomly selected HIV positive individuals and households from the general population. Controlling for unobserved individual characteristics, the findings support the hypothesis of disinhibition behaviors, whereby risky sexual behaviors increase in response to the perceived changes in risk associated with increased access to antiretroviral therapy. Furthermore, men and women respond differently to the perceived changes in risk. In particular, risky behaviors increase for men who believe, wrongly, that AIDS can be cured, while risky behaviors increase for women who believe, correctly, that antiretroviral therapy can treat AIDS but cannot cure it. The findings suggest that scaling up access to antiretroviral therapy without prevention programs may not be optimal if the objective is to contain the disease, since people would adjust their sexual behavior in response to the perceived changes in risk. Therefore, prevention programs need to include educational messages about antiretroviral therapy, and address the changing beliefs about HIV in the era of increasing antiretroviral therapy availability.

This paper—a product of the Human Development and Public Services Team, Development Research Group—is part of a larger effort in the department to better understand the determinants of the HIV/AIDS epidemic. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at ddewalque@ worldbank.org, harounan.kazianaga@okstate.edu, mover@cgdev.org _The Impact Evaluation Series has been established in recognition of the importance of impact evaluation studies for World Bank operations and for development in general. The series serves as a vehicle for the dissemination of findings of those studies. Papers in this series are part of the Bank’s Policy Research Working Paper Series. 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
**Figure 3. Labor supply by educational level**

(a) Women <!-- Start of picture text --> Labour supply by educational level (women)<br>Never attended 1 Primary education .8824 Vocational education<br>.6512<br>.3488<br>.1176<br>General education Secondary general education Secondary special education<br>.8311 .7059 .61<br>.1689 .2941 .39<br>0 1<br>Higher education Postgraduate student 1<br>.5517 .4483<br>0 1 0 1<br>lsupply<br>Graphs by Level of completed education (Q28)<br>1<br>.5<br>0<br>1<br>.5<br>Density 0<br>1<br>.5<br>0<br><!-- End of picture text -->

# (b) Men

<!-- Start of picture text --> Labour supply by educational level (men)<br>Never attended Primary education Vocational education<br>.875 .7742<br>.6286<br>.3714<br>.125 .2258<br>General education Secondary general education Secondary special education<br>.7961<br>.4958 .5042 .3724 .6276<br>.2039<br>0 1 0 1<br>Higher education<br>.5934<br>.4066<br>0 1<br>lsupply<br>Graphs by Level of completed education (Q28)<br>1<br>.5<br>0<br>1<br>.5<br>Density 0<br>1<br>.5<br>0<br><!-- End of picture text --> _Source: own elaboration on the ILO School-to-work transition survey of Azerbaijan._

**Figure 4. Labor supply by age group and gender** (a) Women

# (b) Men

<!-- Start of picture text --> Labour supply by age group (women)<br>Young teenagers (Aged 15-19) Young adults (Aged 20-24)<br>.8446<br>.7007<br>.2993<br>.1554<br>0 1<br>Old-Young (Aged 25-29)<br>.5812<br>.4188<br>0 1<br>lsupply<br>Graphs by ages<br>1<br>.5<br>Density 0<br>1<br>.5<br>0<br><!-- End of picture text --> <!-- Start of picture text --> Labour supply by age group (men)<br>Young teenagers (Aged 15-19) Young adults (Aged 20-24)<br>.787<br>.4929 .5071<br>.213<br>0 1<br>Old-Young (Aged 25-29)<br>.6845<br>.3155<br>0 1<br>lsupply<br>Graphs by ages<br>1<br>.5<br>Density 0<br>1<br>.5<br>0<br><!-- End of picture text --> _Source: own elaboration on the ILO School-to-work transition survey of Azerbaijan._ 34