rafmacalaba/datause-encoder-data huggingface dataset:
19 markets. This was to be done consistently with the Fund’s duty to invest “on a prudent, commercial basis”, in accordance with the relevant legislation.<sup>2</sup> The Guardians, however, considered the request at odds with the Fund’s mandate to maximize return over a long-term horizon without undue risk, and consistent with best practice portfolio management. If allocation to New Zealand assets were to substantially increase beyond the then-current 18 percent share of the total portfolio, the Fund would run the “risks associated with asset concentration, the relative illiquidity of New Zealand assets, and other relevant idiosyncratic risks associated with investing in any single location.” Consequently the Guardians did not offer “an assurance as to how much, if at all, the Fund’s New Zealand assets will increase” based on “the unpredictable nature of future commercial, prudent, investment opportunities”. It was noted that in order “to guarantee an increase to a prescribed percentage would require a modification to the Fund’s commercial objectives” in the relevant legislation. The Guardians concluded that “while local investment activities may produce positive benefits (externalities) in assisting developing New Zealand’s capital markets, we cannot take these externalities directly into account when making an investment decision under our current Act”.<sup>3</sup> _Sources:_

> _1  New Zealand Superannuation Fund_ _<u>http://www.nzsuperfund.co.nz/index.asp?pageID=2145879271; Accessed</u> January 22, 2014. 2 New Zealand Superannuation Fund_ _<u>http://www.nzsuperfund.co.nz/files/Letter%20from%20MoF%20regardng%20NZ%20directive%20and%20fundi ng%20May%2014%202009.pdf</u> ; Accessed January 22, 2014. 3 New Zealand Superannuation Fund_ _<u>http://www.nzsuperfund.co.nz/files/FINAL%20response%20to%20NZ%20investment%20directive%202%20June %202009.pdf</u> ; Accessed January 22, 2014._

Specialized committees are often used to improve performance of the board. These include the audit committee, the remuneration committee, the risk management committee, the corporate governance committee, and the ethics committee. While most SWFs have established audit and executive committees, remuneration, risk management, and corporate governance committees are a relatively new trend. Table 5 summarizes the internal governance arrangements for a small sample of SWFs with domestic investment authority.

19
construct a comparable sample of households that don’t receive remittances, but are otherwise similar in observable characteristics to remittance-receiving households.

We find that after controlling for endogeneity, 30 percent of Burkinabe households receiving remittances from France have concrete houses while 25 percent of comparable households that do not receiving remittances have concrete houses (see figure 4 and annex tables 7 and 8). Households receiving remittance from Cote D’Ivoire are significantly worse off than households receiving remittances from France, and are similar to Burkinabe households that do not receive any remittances.

# **Figure 4. Burkina Faso: Ownership of concrete house of remittance-receiving and other households**

<!-- Start of picture text --> Before matching After matching<br>Comparable<br>30% 30%<br>households not<br>25% receiving remittance<br>(%)<br>16%<br>10% Remittance-receiving<br>9% 9%<br>households (%)<br>No remittances Remittances Remittances Remittances from Remittances from<br>from Cote D'Ivore from France Cote D'Ivore France<br><!-- End of picture text --> Source: Authors’ estimations based on Burkina Faso Core Welfare Indicators Questionnaire Survey 2003.

# **_4.4. Coping strategies of remittance-receiving households versus other households in Ethiopia_**

Ethiopia suffers form extreme poverty and frequent shocks to food security due to recurrent droughts, floods and other natural disasters (Webb 1993, Gray and Mueller 2011). We use the nationally-representative 2004 Welfare Monitoring Survey to examine how remittance-dependent households manage shocks to food security. Migration and remittances are generally understood as a part of coping mechanisms adopted by households facing shocks to incomes and livelihoods (Block and Webb, 2001). Of the 33,302 households in the survey, the majority of households (67 percent) are located in rural areas.

A vast majority (93 percent) of Ethiopian households who report international remittances as their main source of income reside in urban areas. In contrast, only 14 percent of rural households report international remittances as their main source of 17
While these studies shed some light on why open economies are more innovative and dynamic, they also remind of us why integration is controversial. There will be more dislocation in an open, dynamic economy – with some firms closing and others starting up. If workers have good social protection and opportunities for developing new skills, then everyone can benefit. But without such policies there can be some big losers.

Finally, if integration is on balance good for developing countries, it is natural to ask whether one finds evidence for this as well in opinion surveys. The Pew Center for the People and the Press (2003) released a global attitudes survey that provides an interesting perspective on different views of globalization in the developing and developed countries. The Pew Center surveyed 38,000 people in 44 nations, with excellent coverage of the developing world in all regions. In general, there is a positive view of growing economic integration worldwide. But what was striking in the survey is that views of globalization are distinctly more positive in lowincome countries than in rich ones.

While most people worldwide expressed the view that growing global trade and business ties are good for their country, only 28% of people in the U.S. and Western Europe thought that such integration was “very good.” In Vietnam and Uganda, in contrast, the percentages who thought integration was very good were 56% and 64%, respectively. While these countries stood out as particularly pro-globalization, developing Asia (37%) and Sub-Saharan Africa (56%) were far more likely to find integration “very good,” than respondents from rich countries. Conversely, a significant minority (27% of households) in rich countries thought that “globalization has a bad effect on my country,” compared to negligible numbers of households with this negative view in developing Asia (9%) or Sub-Saharan Africa (10%).

38
11 Sexual violence has particularly serious consequences for women’s sexual and reproductive health. It may lead to gynecological problems, unwanted pregnancy, chronic pelvic pain, unsafe abortion, and sexual dysfunction; intimate partner violence has been linked to similar outcomes, as well as complications during pregnancy, miscarriage and low birth-weight (Campbell, 2002). Sexual abuse in childhood and adolescence has been linked to a higher risk of subsequence victimization, early sexual activity, substance abuse, and multiple sexual partners (Felitti et al., 1998; Heise, Ellsberg, and Gottemoeller, 1999; Walker et al., 1999) _._ Many women consider the psychological consequences of physical, sexual and emotional abuse to be even more serious than its physical effects. Recent results from the WHO MultiCountry Study on Women’s Health and Domestic Violence found that women with a history of physical and/or sexual partner abuse were as much as three times more likely to consider and/or attempt suicide. In all 10 countries surveyed, women who had experienced intimate partner violence at any point in their lives were significantly more likely to be suffering from symptoms of emotional distress at the time of the interview (World Health Organization, 2004).

Researchers have also documented negative outcomes among children of women who experience violence. For example, researchers in Nicaragua found that children of women who were physically and sexually abused by their partners were six times more likely than other children to die before the age of five, with one third of all child deaths in this setting being attributed to partner violence (Åsling-Monemi et al., 2003). Boys and girls who witness violence in the home may be at increased risk for emotional and behavioral problems, such as anxiety, depression and violence towards their peers (Jaffe and Sudermann, 1995) and, in the case of boys, for perpetrating intimate partner violence and/or sexual violence as adults (Straus and Gelles 1986; Ellsberg, Peña et al. 1999; Kishor and Johnson 2004).

# **1.5  Socioeconomic Costs of Gender-Based Violence**

GBV poses significant costs for the economies of developing countries, including lower worker productivity and incomes, lower rates of accumulation of human and social capital, and the generation of other forms of violence both now and in the future. This section will present methodological options for measuring the costs of violence, as well as some estimates produced by these methodologies.

Before presenting the methodological options, however, a more fundamental question must be addressed: why produce cost estimates at all? GBV is already recognized as a serious human rights issue, a priority issue for women’s organizations, and an important public health issue. What additional purpose is served by producing cost estimates? The answer is simple: estimates of economic costs facilitate the “dimensioning” of the issue, i.e., determining the relative importance of GBV violence among the panoply of pressing development issues.
**Table 4: Relationship between Indoor PM2.5 and Health Outcomes**

|**A. Child Height-for-Age**|**Bir**<br>**Heigh**<br>|**th to 36 Months**<br>**t-for-Age (z-score)**<br><br>||**Bi**<br>**Heig**<br>|**rth to 76 Mon**<br>**ht-for-Age (z-**<br>|**ths**<br>**score)**<br>|
|---|---|---|---|---|---|---|
||**(1)**|**(2)**<br>**(3)**||**(4)**|**(5)**|**(6)**|
|ln(Maximum PM2.5 level)|-0.638**|-0.471**<br>-0.569**||-0.304**|-0.239**|-0.295***|
||(0.252)|(0.177)<br>(0.239)||(0.123)|(0.110)|(0.108)|
|Individual Level Controls||y<br>y|||y|y|
|Household Level Controls||y||||y|
|Observations|53|53<br>53||159|159|159|
|**B. Respiratory Symptoms**|**and Physical F**<br>**Chil**|**unctioning**<br>**dren**||**Adult**|**Cooks**||
||**N.**|**Any**|**N.**|**Any**|**Any ADL**|**N. ADL**|
||**Symptoms**<br>**(1)**|**Symptoms**<br>**(2)**|**Symptoms**<br>**(3)**|**Symptoms**<br>**(4)**|**limitations**<br>**(5)**|**limitations**<br>**(6)**|
|ln(Maximum PM2.5 level)|-0.302|-0.007|-0.010|-0.004|-0.015|0.093|
||(0.246)|(0.033)|(0.357)|(0.026)|(0.041)|(0.239)|
|Individual Level Controls|y|y|y|y|y|y|
|Household Level Controls|y|y|y|y|y|y|
|Observations|513|513|202|202|202|202|

Notes: Table reports results from regressions of health outcomes on log maximum indoor PM2.5 concentrations. Panel A examines child height for age for children under 36 months old in columns 1-3 and under 76 months old in columns 4-6. Panel B. examines respiratory symptoms for children birth to 15 years in columns 1 and 2 and adult cook outcomes in columns 4 through 6. Individual level controls include a cubic polynomial in age, sex, mother's height and age, and father's age. Household level controls include household size and demographic composition, age, education and sex of the household head, dwelling characteristics, site fixed effects, and a composite wealth index. Standard errors robust to clustering at the household level used for child outcomes and community level used for adult outcomes. *** p<0.01, ** p<0.05, * p<0.1

# **6.2 Respiratory symptoms, adult ADLs, and pollution**

While there is suggestive evidence of a pollution–height-for-age link at the observed levels of particulate concentration, we find no such link for respiratory symptoms or activities of daily living. Panel B of Table 4 presents estimates for summary measures of child symptoms in columns 1 and 2, and adult cook outcomes in columns 3 through 6. All regressions include additional individual and household level controls.

Of the six estimates, none is statistically significant. The effects do not appear to be driven by small sample size concerns, as many of the effects are economically small in magnitude.

Taken together with Panel A, the null findings in Panel B suggest a plausible pollution-health mechanism that would lead to growth effects for young children, even without observed health benefits for adult cooks and older children. This pattern is plausibly consistent with physiological scarring attributed to cumulative exposure to high levels of particulate matter in the past for adults 21
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is a function of the exporter size. Hallak (2006) focuses on the demand side and studies the relationship between per capita income and aggregate demand for quality. Analyzing bilateral trade flows among 60 countries, he finds that rich countries import relatively more from countries which produce high quality goods.

All theoretical and empirical studies presented above argue that differences in factor endowments, technology, or consumption preferences between countries constitute the main driving force behind trade of goods of different quality. Building on these differences between countries, the studies remain silent about the role of vertical product differentiation for trade between similar economies. The first question therefore to ask is to what extent qualityrelated aspects are crucial for trade between similar economies. We try to answer this question taking the case of trade between the EU 15 and analyze the trade pattern with respect to quality between this relatively homogeneous group of countries.

As commonly done in the literature on quality trade, we assume that unit values provide a reasonable measurement of vertical product differentiation.<sup>5</sup> Table 1 provides a summary of several key indicators on quality trade based on unit values of the highest disaggregated trade available.<sup>6</sup>

**Table 1:** **_Coefficient of Variation and Share of Quality Trade_**

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
||Coef.Var|±10 %|±20 %|±30 %|
|EU 15|70.18 %|85.66 %|72.90 %|61.29 %|
|Obs.|680,656|680,656|680,656|680,656|

Notes: Coef. Var. is the abbreviation for the coefficient of variance expressed in percentage. EU 15 stands for all export flows between EU 15 countries. For the columns presenting the share of quality trade, the numbers in percentage report the share the lies outside the range of ± 10 %, ± 20 %, and ± 30 % respectively.

Column (1) in Table 1 reports the average value of the coefficient of variation of all available unit values per product for trade between the EU 15.<sup>7</sup> As explained above, the vast majority of trade models would predict that the coefficient of variation of unit values for each product

> 5 See Greenaway (1995) for a detailed discussion on the use of unit values as a measure of quality.

> 6 EUROSTAT offers detailed trade data on the 8 digit level (more than 10.000 different products) according to the Combined Nomenclature.

> 7 The coefficient of variation is defined as the ratio between the standard deviation and the mean of the population. It yields a number without dimension that allows us to calculate the mean of the coefficient of variation over all product lines and exporting countries. We report the final result as percentage multiplying the coefficient of variation by 100.

3
|TABLE4. OLS Estimation|of Wage Eq|uations in the<br>1993|Public and|Private Secto|r in 1993 and<br>2006|2006|
|---|---|---|---|---|---|---|
||Coef.|Std. Err.|P>t|Coef.|Std. Err.|P>t|
|Public|0.193|0.181||−0.052|0.124||
|Years of schooling|0.012|0.010||0.038|0.003|***|
|Years of experience|0.056|0.010|***|0.022|0.003|***|
|Square of experience|−0.118|0.024|***|0.000|0.000|***|
|Male|0.276|0.074|***|0.230|0.024|***|
|Vocational training|−0.332|0.195|*|0.135|0.040|***|
|Public * Years of schooling|0.024|0.013|*|0.047|0.009|***|
|Public * Years of experience|−0.035|0.016|**|0.006|0.007||
|Public * Square of experience|0.092|0.045|**|0.000|0.000||
|Public * Male|−0.184|0.095|*|−0.229|0.039|***|
|Public * Vocational training|0.260|0.203||−0.226|0.052|***|
|Constant|−0.321|0.107|***|0.771|0.045|***|
|Observations||856|||3893||
|R-squared||0.129|||0.264||
|Mean squared error||0.62|||0.55||

_Source:_ Author's calculations based on VLSS and VHLSS data.

# _Our model_

We now turn to the estimation of our model. The lack of observations leads us to adopt a simple estimation method, the nonlinear least squares (minimum distance estimation) method, which has better small-sample properties than the Generalized Method of Moments used by Lemieux (1998). The model estimates are shown in table 5.

Very different patterns emerge for the 1993–1998 and 2002–2006 periods. In the 1993–1998 panel, the returns to the workers' comparative advantage in the public as compared with the private sector (α) are significantly inferior to one. In the 2002–2006 panel, they are not significantly different from one, and the point estimate is greater than one. This change suggests that the public sector, which initially offered lower returns on workers' comparative advantage than the private sector, has now adopted compensation patterns that reward workers at least as much. Interestingly, the point estimate of ηt is also rising but is never significantly different from zero. Therefore, the higher pay in the 20
# **Measuring Poverty Dynamics with Synthetic Panels Based on Cross-Sections**

Hai-Anh H. Dang and Peter F. Lanjouw<sup>*</sup>

**Keywords:** transitory and chronic poverty, mobility, welfare, synthetic panels JEL Codes: C53, D31, I32, O15

> _*_ Dang <u>(hdang@worldbank.org; corresponding author) and Lanjouw (p.f.lanjouw@vu.nl) are</u> respectively economist and professor with the Poverty and Inequality Unit, Development Research Group, World Bank, and VU University Amsterdam. We thank  Francois Bourguignon, Alan Dorfman, Chris Elbers, Francisco Ferreira, Gary Fields, Paul Glewwe, Bill Greene, Bo Honore, Dean Jolliffe, Aart Kraay, Christoph Lakner, Yue Man Lee, Michael Lokshin, David McKenzie, Reema Nayar ,Tuoc Van Phan, Sergiy Radyakin, Carolina Sanchez-Paramo, Renos Vakis, Roy van der Weide, Nobuo Yoshida, and participants at meetings of the Econometric Society, International Association for Applied Econometrics, International Conference on Panel Data, and seminars at IFPRI, University of New South Wales, and World Bank for helpful discussions on earlier versions of this paper. We further thank Renos Vakis and Leonardo Lucchetti for their help with the Peruvian data.
Table 2: Multiplier associated with spending increases

|Quarters|1|4|8|12|20|Peak|
|---|---|---|---|---|---|---|
||Model w<br>|ith exogen<br>|ous factor<br>|s<br>|||
|Impact multiplier|0.21*|0.00|-0.11|-0.08|0.07|0.21*(1)|
|Govt. spending|1.00*|0.85*|0.64*|0.48*|0.25*||
|Net tax revenue|-0.07*|-0.63*|-0.66*|-0.48*|-0.17*||
|Cumulative multiplier|0.21*|0.11|0.01|-0.04|-0.03|0.21*(1)|
||Model w|ithout exo|genous fac|tors|||
|Impact multiplier|0.26*|-0.50*|-1.02*|-1.19*|-1.03*|0.26*(1)|
|Govt. spending|1.00*|0.94*|0.79*|0.66*|0.44*||
|Net tax revenue|0.02|-0.93*|-1.39*|-1.47*|-1.22*||
|Cumulative multiplier|0.26*|-0.14*|-0.55*|-0.85*|-1.22*|0.26*(1)|

Notes: Each panel of this table provides the multiplier associated with a one-dollar increase in government spending in the first quarter. The first and fourth rows represent the impact multiplier and the cumulative multiplier, respectively, for each quarter. The multiplier given here is the median and * denotes that 0 does not belong to the confidence region. The second and third rows represent the response of government spending and net tax revenue. The last column reports the maximum multiplier, and numbers in brackets denote the quarters in which the maximum is observed.

upon impact. With the decline in tax revenue at a lower rate than in the previous case, the multiplier now gradually becomes positive in the medium term.

Overall, except the first quarter, the negative effects of net taxes on GDP tend be larger when exogenous controls are included in the VAR. These results are in line with the expectations. Indeed, when there is no exogenous control variable in the VAR, a onedollar increase in tax revenue might come from changes in tax policy, oil prices, and U.S. GDP. Because changes in tax revenue coming from oil prices and U.S. GDP fluctuations do not result from domestic changes to tax rates, they might not have significant effects on GDP. Therefore, the part of the impact coming from changes to tax rates might not be large enough. Controlling for these exogenous changes might therefore increase the negative effects of an increase in net tax revenue on GDP, as this increase results entirely from changes in tax policy.

# **3.3 Sub-period analysis**

To test the stability of the impact of fiscal policy shocks on GDP over time, I split the sample at the 4<sup>_th_</sup> quarter of 1990 in order to have two sub-periods with relatively the same size. In addition, the Bank of Canada introduced an inflation-targeting regime in the first quarter of 1991 to stabilize inflation. The early 1990s was also a time of rapid — globalization, with greater trade with the introduction of the North American Free — Trade Agreement and capital mobility. These changes could have affected how the fiscal policy shocks propagate through the Canadian economy. In the following, I study the impact of the government spending and net tax revenue shocks over both sub-periods while controlling for changes in the state of the U.S. economy and world oil prices.

13