rafmacalaba/datause-encoder-data huggingface dataset:
tices. These practices were measured using items describing parent-child relationships adapted from the Longitudinal Study of Australian Children (Zubrick, Smith, Nicholson, Sanson, & Jackiewicz, 2008). The questions covered a range of possible practices. Parenting practices are specific behaviors that parents use in their interactions with their child. These include, for example, using reprimands, giving praise, showing physical affection and setting and keeping with rules for behavior (Bornstein & Zlotnik, 2008; L. O. Walker & Kirby, 2010).<sup>11</sup> Following a recent narrative review of parenting, three hierarchical summary constructs are proposed: warmth, consistency, and hostility (Jansen, Daniels, & Nicholson, 2012). We compute these constructs by calculating within each of them the proportion of items the caregiver responds as having undertaken frequently.

Many dimensions of parenting have been shown to influence child development, although different terms are often used to describe overlapping or similar constructs. Generally, children show better developmental outcomes when exposed to parenting that is high on the dimensions of warmth, consistency, inductive reasoning and self-efficacy and low on the dimensions of irritability, hostility and over-protectiveness (Bayer et al., 2011; Bradley et al., 1989; Chang, Schwartz, Dodge, & McBride-Chang, 2003; Chao & Willms, 2002; Paterson & Sanson, 1999; Pettit & Bates, 1989). Parenting styles are multidimensional categories of behaviors and attitudes which classify parents according to where they lie on the distributions of some specific parenting dimensions (Darling & Steinberg, 1993). One of the most well-known classifications of parenting style is that applied by Baumrind and others (Baumrind, 1991; Darling & Steinberg, 1993; Maccoby & Martin, 1983) defining four parenting styles based around levels of over-controlling and responsive parenting: authoritative (high control, high responsiveness), authoritarian (high control, low responsiveness), indulgent/permissive (low control, high responsiveness), and uninvolved/neglectful parenting (low control, low responsiveness). In the Anglo population in Western societies, authoritative parenting has been most consistently associated with positive socioemotional competence, cognitive and health outcomes in children (Baumrind, 1991; Bornstein & Zlotnik, 2008; Jackson,

> 11The psychology literature has paid close attention to these practices, particularly in the case of corporal punishment and spanking. See Gershoff and Grogan-Kaylor (2016) for a review and Putnick et al. (2012) for an analysis of data from a cross-section of countries.

13
|**Table 6: Which Factors are Associated with Higher Business Pr**|**actices?**|||||||
|---|---|---|---|---|---|---|---|
|Dependent variable: Business Practices Score||||||||
|Years of education of owner|0.012***||||||0.011***|
||(0.000)||||||(0.000)|
|Digitspan recall|0.010***||||||0.009***|
||(0.001)||||||(0.001)|
|Raven test score|0.003***||||||0.003***|
||(0.001)||||||(0.001)|
|Owner is male|0.026***|0.029***|0.027***|0.015**|0.029***|0.026***|0.008|
||(0.007)|(0.007)|(0.007)|(0.007)|(0.007)|(0.007)|(0.007)|
|Age of owner|‐0.001***|‐0.002***|‐0.002***|‐0.002**|* ‐0.002***|‐0.003**|* ‐0.001***|
||(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|
|Father owned a business||0.016***|||||0.011**|
|||(0.005)|||||(0.005)|
|Mother owned a business||0.015***|||||0.011**|
|||(0.006)|||||(0.005)|
|Has between 1 and 4 competitors|||0.005||||0.013|
||||(0.010)||||(0.009)|
|Has between 5 and 9 competitors|||‐0.003||||0.008|
||||(0.010)||||(0.010)|
|Has between 10 and 20 competitors|||‐0.002||||0.005|
||||(0.010)||||(0.010)|
|Has 21+ competitors|||0.010||||0.016|
||||(0.010)||||(0.010)|
|Most important competitor is located within 1 km of business||||‐0.013|||‐0.007|
|||||(0.008)|||(0.008)|
|Would take less than a day for customer to replace them|||||‐0.017***||‐0.003|
||||||(0.007)||(0.006)|
|1 to 4 paid workers||||||0.101***|0.087***|
|||||||(0.005)|(0.005)|
|5 to 9 paid workers||||||0.143***|0.119***|
|||||||(0.009)|(0.008)|
|10 to 14 paid workers||||||0.172***|0.143***|
|||||||(0.010)|(0.010)|
|15 to 20 paid workers||||||0.190***|0.156***|
|||||||(0.014)|(0.014)|
|21+ paid workers||||||0.235***|0.193***|
|||||||(0.014)|(0.013)|
|Owner started business themselves|||||||0.019***|
||||||||(0.007)|
|Sample Size|20162|20162|20162|20162|20162|20162|20162|
|Notes:<br>Robust standard errors in parentheses. *, **, *** denote signif<br>All regressions also control for sector, country, and for missing|icance at t<br>values of|he 10, 5 an<br>the control|d 1 percen<br>variables|t levels re<br>where ne|spectively.<br>eded.|||

36
28

**Table 7:** The effect of visa provision on the bilateral migration stocks: Skilled _versus_ other sector migration.

|Dep var:|Unsk|illed|Ski|lled|
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|Visa|0.164***|0.165***|0.086*|0.089*|
||(0.058)|(0.058)|(0.048)|(0.048)|
|RTA|-0.092**|-0.092**|-0.014|-0.013|
||(0.043)|(0.043)|(0.042)|(0.042)|
|Schenghen||0.052||0.097|
|||(0.104)||(0.086)|
|GDP diference (ln)|0.060**|0.061**|0.038*|0.039*|
||(0.026)|(0.026)|(0.023)|(0.023)|
|Estimator|PPML|PPML|PPML|PPML|
|Country-Year Fixed Efects|Yes|Yes|Yes|Yes|
|Country-Pair Fixed Efects|Yes|Yes|Yes|Yes|
|Sample period|2000-2010|2000-2010|2000-2010|2000-2010|
|Observations|4,164|4,164|4,033|4,033|
|Pseudo R-squared|0.99|0.99|0.99|0.99|

Note: Dependent variable is the stock of immigrants in country _j_ originating from _i_ . Data on bilateral stock of migrants by macro-occupation are from the OECD DIOC dataset `https: //www.oecd.org/els/mig/dioc.htm` . Skilled immigrants are those in ISCO occupation 1, 2 and 3. Robust standard errors in parentheses. ***, **, * significantly different from 0 at the 1%, 5%, and 10% levels respectively.
This mechanism sets a PV capacity installation growth path which is dependent on the PV capacity installed the year before, and results in a decrease or an increase of the FIT rates according respectively to the percentage that the corridor path was exceeded or unmet. As PV capacity installations were superior than planned by government in 2010, the FIT rates were decreased by 13% on January 1<sup>st</sup> , 2011 to reflect the decrease in PV costs.

The FiT is regarded as the key driver for recent growth of grid connected solar power, both CSP and grid connected PV. However, some existing studies, such as Couture and Cory (2009), identify several concerns with the FiT. FITs put upward pressure on electricity rates, at least in the near to medium term in order to significantly scale up the deployment of such technologies. FiT policies guaranteeing grid interconnection, regardless of location on the grid, increase transmission costs if projects are sited far from load centers or existing transmission or distribution lines<sup>18</sup> . Similarly, FiT policies designed to periodically adjust to account for changes in technology costs and market prices over time pose a challenge with respect to balancing the purpose of the tariff – increasing utilization of the beneficiary technologies – and fiscal cost, especially as the authorities can only guess at the appropriate tariff adjustments. Changing payment levels increase uncertainties to investors, and political pressures to hold down payments increase overall market risk. In Germany, for example, there was political pressure to cap the policy or speed its rate of decline (Frondel et al., 2008; Podewils, 2007).

# **5.2. Investment tax credits**

Different types of investment tax credits have been implemented in several jurisdictions around the world to support solar energy. In the United States, for example, the federal government provides an energy investment tax credit for solar energy investments by businesses equal to 30% of expenditures on equipment to generate electricity, to heat or cool and on hybrid solar lighting systems. Besides the investment tax credit, the US federal government provides an

> 18 Couture and Cory also note that while the FIT provides incentives to investors by guaranteeing reasonable rates of return on investment, it does not directly subsidize high up-front costs.  This could limit increased solar power financing in situations in which capital generally is scarce, as is the case in a number of developing countries.  On the other hand, as discussed later , subsidies of initial investment costs provide greater relative benefits to less efficient and less well-capitalized firms, which is inconsistent with the interest in bringing down the cost of the technologies over time.  In addition, domestic capital scarcities in the power sector can stem in part from stringent limits on foreign investment in the sector, cutting off the country from a global pool of capital for increased generation capacity generally.

26
- Kudamatsu, M. (2012): “Has Democratization Reduced Infant Mortality in Sub-Saharan Africa? Evidence from Micro Data,” _Journal of the European Economic Association_ , 10(6), 1294–1317.

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(2012): “Administrative Divisions of Countries ("statoids"),” .

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- 1–20.

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- MRDS (2005): “Mineral Resources Data System: U.S. Geologival Survey,” Reston, Virginia.

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28
We estimated our model with linear, logarithmic and quadratic specifications and retain the quadratic one as it produced the best fit. The graphical output of a semi-parametric estimation further justifies the choice of the quadratic model (see figure 3).

Model 3.1 is tested using data from a comprehensive country-year panel of aid receiving countries from 1996 to 2008. In robustness tests, however, we employ three alternative sample restrictions. First, we drop all observations for a country after its last DPL containing PSG conditions has closed. Second, we follow Easterly (2005) in limiting the sample to countries that received at least one DPL with PSG-related conditions. Third, we estimate the model excluding Argentina (a strong outlier) from the sample.

# _3.1. correction for endogeneity: two approaches_

When analyzing the association of World Bank lending with the quality of public sector governance, we have to take into account a potential selection bias problem. That is, countries often receive policy loans because of governance deficiencies, so the coefficient on DPL conditions may be biased downward when examining its impact on policy outcomes (Easterly, 2005). On the other hand, the coefficient may be biased upward, if loans (and their associated conditions) tend to go to motivated governments that would have reformed even in the absence of support. The basic rationale of a DPL is that the prospect of receiving a loan motivates a government to implement a set of “prior actions” or policy conditions negotiated with the Bank, and funds are then disbursed in anticipation of further reforms. Conceivably, however, governments might have implemented a similar set of measures whether or not a DPL with PSG conditions had been negotiated with the Bank.

Correcting for this problem calls for a robust identification strategy, which we implement in two alternative ways. First we estimate equation 3.1 with system GMM (Arellano and Bover, 1995; Blundell and Bond, 1998) and instrument for number of conditions with its lagged differenced values. The Arellano and Bond (1991) tests indicate _AR_ (3) autocorrelation. Hence, we lag number of conditions by four periods. Furthermore, as the number 10
|Table B.2: Fiscal (pro)cyclicality of individual inco|me tax rates, whole sa|mple (2000-2016):|Impacts of le|vel playing fiel|d, natural resou|rces, and other|factors||||
|---|---|---|---|---|---|---|---|---|---|---|
|Dependent variable: Individual income tax|(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|
|Cyclicality of real GDP|-0.200**<br>(0.083)|0.121<br>(0.434)|0.408<br>(0.816)|-0.096<br>(0.163)|-0.065<br>(0.169)|-0.096<br>(0.163)|-0.384***<br>(0.084)|-0.060<br>(0.442)|8.195<br>(12.065)|0.377***<br>(0.034)|
|**Equality of conditions**|||||||||||
|Crgdp*power.distribution|-0.051<br>(0.138)||||||||||
|Crgdp*resource.distribution||-0.396<br>(0.684)|||||||||
|Crgdp*ethnicandrel.stability|||-0.201<br>||||||||
||||(0.293)||||||||
|**Natural resources**|||||||||||
|Crgdp*resource.dependant (bd)||||-0.256<br>(0.182)|||||||
|Crgdp*resource.rich (bd)|||||-0.288<br>(0.188)||||||
|Crgdp*resource dependant and rich||||||-0.255<br>0182|||||
|||||||(.)|||||
|**Other factors**|||||||||||
|Crgdp*elections|||||||0.176<br>(0.188)||||
|Crgdp*debt.ratio||||||||-0.021<br>(0.036)|||
|Crgdp*rigidity|||||||||-1,598.647<br>(2,139.051)||
|Crgdp*fiscal space||||||||||-30.251***<br>(1.268)|
|Constant|36.452***|22.366**|-0.766|2.008**|2.007**|2.008**|2.006**|3.433***|44.874***|2.934***|
||(1.904)|(8.656)|(4.602)|(0.891)|(0.891)|(0.891)|(0.892)|(1.067)|(4.441)|(0.877)|
|Adjusted R-squared|0.831|0.835|0.880|0.874|0.874|0.874|0.874|0.879|0.778|0.879|
|Rmse|4.326|4.279|4.287|4.327|4.327|4.327|4.330|4.270|5.559|4.240|
|Joint significance (p-value)|0.003|0.097|0.000|0.002|0.000|0.000|0.000|0.000|0.433|0.000|
|CD test (p-value)|0.000|0.000|0.000|0.000|0.000|0.000|0.000|0.000|0.000|0.000|
|Order of integration|I(0)|I(0)|I(0)|I(0)|I(0)|I(0)|I(0)|I(0)|I(0)|I(0)|
|Cluster|country|country|country|country|country|country|country|country|country|country|
|Covariates|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Observations|689|689|746|826|826|826|826|814|399|823|
|# countries|47|47|48|48|50|50|50|50|26|50|

Notes. Standard errors (in parentheses) clustered at the country level. All interactive variables are also introduced in level but not reported to save space. Coefficients attached to cyclicality of GDP or its interactions are multiplied by 10000. All regressions include the volatility of the terms of trade, BD for missing data in real GDP and real expenditure series, BD for five years HP cycle correction. See Table A.3 for further discussion on variables definition. *** p<0.01, ** p<0.05, * p<0.1.

31
# The Power and Roots of Aspirations<sup>∗</sup>

A Survey of the Empirical Evidence Anna Fruttero International Monetary Fund Noël Muller World Bank Óscar Calvo-González World Bank Originally published in the Policy Research Working Paper Series on _July, 2021._ This version is updated on _August 2021._ To obtain the originally published version, please email prwp@worldbank.org.

**Keywords** : Aspirations, education, employment, individual behavior, measurement, poverty, role models, inequality.

**JEL** : D91, I24, J24, O15, Z1

> ∗ We thank Samantha de Martino, Vijayendra Rao, and Debraj Ray for feedback. Contacts: Anna Fruttero <u>(afruttero@imf.org; afruttero@worldbank.org), Noël Muller (nmuller@worldbank.org; noel.muller@hotmail.fr), and Óscar</u> Calvo-González (ocalvogonzalez@worldbank.org).
Indonesia and the Phillipines are examples of French civil law countries where enforcement is actually faster than in many other countries.

# <u>Africa</u>

<!-- Start of picture text --> Figure 4. Perceptions of Judicial Efficiency Figure 5. Formalism Index<br>3.70 3.59<br>10.00 9.16 8.55 3.60<br>9.008.00 7.50 7.65 3.50 3.38<br>7.00 6.31 3.40 3.28<br>6.00 5.45 5.33 3.30<br>5.00 3.20<br>4.00 3.10 3.05<br>3.00 1.79 3.00<br>2.00<br>2.90<br>1.00<br>0.00 2.80<br>Judicial Citizens' Access Enforcement Control of 2.70<br>Efficiency Index to Justice Index Corruption Index Check Eviction<br>High Income Countries African Countries High Income Countries African Countries<br><!-- End of picture text --> _Fig.3 Sources: Judicial Efficiency Index: ICRG; Citizens’ Access to Justice: World Business Environment Survey; Enforcement Index: Business Environmental Risk Intelligence; Control of Corruption: ICRG. Fig.4 Source:World Bank 2001 and Djankov et al. 2001_ A close look at the data on procedural complexity shows that there is a significant difference in the level of procedural complexity in Africa relative to the high income countries in the sample (at the 5% confidence level) and particularly in the statutory regulation of evidence in Africa<sup>34</sup> . The sample of African countries shows a higher degree of formalism relative to the E. Asian sample. A comparison of common law African and rich countries shows that despite the similar legal background, there is a substantial difference in the level of statutory regulation of evidence, the degree of intervention by the appellate courts (control of superior review), and the degree of other statutory interventions – all significant at the 5% confidence level. The common law African countries have less procedural complexity than the civil law ones and faster dispute resolution and better control of corruption.

> 34 In this sample, Botswana, Ghana, Kenya, Malawi, Namibia, Nigeria, South Africa, Swaziland, Tanzania, Uganda, Zambia and Zimbabwe follow the English common law tradition, while Cote d’Ivoire, Egypt, Mozambique, Senegal, and Tunisia follow the French civil law system.

32
likely to tighten up environmental policy in sectors that are facing strong import competition, then if this is not accounted for one might falsely conclude that weak environmental policy leads to reduced international competitiveness.

Much of this recent work has found evidence in support of the weak version of the pollution haven hypothesis – that is, in many recent studies more stringent environmental regulation in the manufacturing sector has a statistically significant negative effect on various measures of competitiveness in the affected sectors.<sup>6</sup> For example, Becker and Henderson (2000) and several other studies have found that increases in the stringency of environmental regulations induced by the US Clean Air Act tend to reduce the likelihood that a new plant will locate in the affected jurisdiction. Keller and Levinson (2002) found that high abatement costs have a negative effect on foreign investment inflows, while Hanna (2010) found evidence that the US Clean Air Act induced some multinationals to relocate production away from affected jurisdictions. Ederington and Minier (2003) and Levinson and Taylor (2008) found that higher abatement costs tend to have a positive effect on net imports (or equivalently, reduce net exports) in affected sectors.

There are a few studies that use data from newly industrializing countries, mostly focusing on incoming foreign investment. The results here have been mixed, with most studies finding little or no evidence that environmental policy affects the pattern of investment, but with some finding a negative effect and others a positive effect. Dean, Lovely, and Hwang (2009) used data on variations across provinces in China in charges for water pollution to determine whether the stringency of environmental policy affected incoming foreign investment. They found that more stringent regulation had a negative effect on investment from ethnically Chinese source countries (Hong Kong SAR, China; Macao; and Taiwan, China) in highly polluting sectors. However, environmental policy had no statistically significant effect on investment from other countries. Eskeland and

> 6 For reviews of this work, see Brunnermeier and Levinson (2004) and Copeland and Taylor (2004).

11
- 32 -

# Table (3.4)

Rates of change in some of Sudan's key macroeconomic indicators (percent)

|S|Money<br>upply(M1)|Official<br>Reserve|Domestic<br> <br>Credit|Inflation<br>%\ACPI|Real<br> <br>GDP|Official<br>Deval.|Depr. in<br>B.M. rate|RER_1i_|
|---|---|---|---|---|---|---|---|---|
|1971|7.09|4.08|16.83|2.85|6.94|0.00|0.00|-5.57|
|1972|16.64|109.80|<br>19.81|6.32|-2.14|0.00|2.86|-5.36|
|1973|21.61|72.90|11.76|9.67|-8.07|0.00|2.78|-10.24|
|1974|35.08|32.43|29.87|12.20|10.09|0.00|0.00|-19.44|
|1975|18.59|40.41|58.52|6.65|12.67|0.00|0.00|-14.17|
|1976|24.49|28.49|28.15|1.42|18.41|11.90|2.70|-3.33|
|1977|41.92|161.31|<br>31.66|1.12|15.19|36.17|-2.63|-23.84|
|1978|27.46|52.12|24.02|12.15|-1.56|32.81|8.11|5.30|
|1979|32.04|36.60|22.71|10.84|-10.37|15.29|25.00|-7.22|
|1980|31.19|-18.21|21.63|26.00|0.95|-11.22|26.00|0.63|
|1981|39.50|99.34|34.40|17.99|2.09|17.24|42.86|15.34 1|
|1982|36.59|4.37|16.08|10.76|12.68|69.61|44.44|12.67|
|1983|11.72|102.30|29.47|14.04|2.06|21.39|7.69|-15.58|
|1984|18.33|13.37|19.53|16.57|-5.01|16.19|21.43|-7.37|
|1985|49.94|114.52|36.45|1.52|-6.28|164.34|47.06|-0.00|
|1986|41.12|34.10|39.14|8.00|9.73|-7.75|24.00|1.61|
|1987|32.82|21.82|38.99|7.69|1.13|12.77|19.35|-6.94|
|1988|44.41|-2.43|33.26|14.02|-1.90|50.82|21.62|-26.16|

Notes: 1/ RER = exchange rate for exports/price of nontradables (decrease indicates a real appreciation) Sources IMF International Financial Statistics, Picks World Currency Yearbook, Elbadawi (1988)