rafmacalaba/datause-encoder-data huggingface dataset:
**Figure 4: Impact of demographic changes on growth of capital stock (average annual rate), 2011-30**

4.50 <!-- Start of picture text --> 4.00<br>3.50<br>3.00<br>2.50<br>2.00<br>1.50<br>1.00<br>0.50<br>0.00<br>-0.50<br>-1.00<br>Note: Full age structure freeze scenario results subtracted from high growth baseline.<br>Figure 5: Impact of demographic changes on changes in capital to worker ratios, 2011-30<br>1.50<br>1.00<br>0.50<br>0.00<br>-0.50<br>-1.00<br>-1.50<br>-2.00<br>Percentage Points<br>Ethiopia Zimbabwe Burkina Faso Rwanda Senegal Uganda Malawi Ghana Cameroon Zambia Madagascar Kenya Rest of SSA Côte d’Ivoire Mozambique Tanzania Nigeria Botswana South Africa SSA<br>Simple Difference in K/L Ratio<br>Ethiopia Burkina Faso Senegal Cameroon Zambia Rest of SSA Ghana Côte d’Ivoire Uganda Rwanda Kenya Zimbabwe Nigeria Malawi Madagascar Mozambique Tanzania Botswana South Africa SSA<br><!-- End of picture text --> Note: Full age structure freeze scenario results subtracted from high growth baseline. Source: Simulation results

**Figure 5: Impact of demographic changes on changes in capital to worker ratios, 2011-30**

Note: Full age structure freeze scenario results subtracted from high growth baseline. Source: Simulation results Note: K/L is defined as the ratio of capital stock to the number of workers While demographic change can clearly boost aggregate growth through the model’s labor and savings channels, the impacts on consumption are less intuitive. In any given country, a household’s marginal propensity to consume is strongly influenced by the country’s savings behavior, which in turn is a function of past behavior, real income GDP per capita growth, and demographics (equation 2). So, all else equal, as dependency ratios fall and savings as a share of GDP rises in SSA, consumption growth can be expected to be dampened. This can be illustrated by considering the real consumption per capita growth rate of Sub-Saharan Africa as a whole. Real consumption per capita grows at a rate of 3.3 16
a matter of interest on its own. Health is an important aspect of human welfare, and health inequality is relevant to the equity of health, a broader notion (Sen, 2002). Given that child health indicators are important in predicting the future social standing of the child (Nystrom Peck, 1992; Montgomery et al., 1996), the existence of child health inequality in itself is indeed a concern.

In what follows, we shall focus on the decomposition analysis of inequality indicators. The analysis we carry out is different from most other studies on health inequality decomposition in at least three respects. First, despite the growing literature on health inequality, there have been relatively few studies carried out at a spatially disaggregated level, especially in developing countries. The methodology we developed in this study allows us to analyze health inequality at a level of small geographic areas even in the absence of a large number of observations of health indicators collected at that level.

Second, while the majority of health inequality literature uses mortality data, we use the standardized height and weight. Because death is a rare event, it may not be the best indicator at a very disaggregated level. Also, the probability of death is influenced by the individual’s experiences over the course of his/her life. This makes it difficult to compare populations with different demographic groups. Standardized height and weight for children have some advantages here. Moreover, anthropometric indicators are likely to be more reliable than mortality data in countries like Cambodia where vital records are not fully maintained. Pradhan et al. (2003) discusses additional advantages of the standardized height measure.<sup>13</sup> Third, we emphasize direct policy implications of inequality for targeting. Geographic targeting is meaningful only when there exists spatial heterogeneity in malnutrition or consumption. Hence, the between-location component of overall inequality is relevant to potential gains from geographic targeting. In many of the health inequality studies, the focus

> 13Pradhan et al. (2003) prefer height to weight because too much weight is obviously not good for health. Given that less than 1 percent of the children under five is overweight in Cambodia, this is a minor concern in this study.

22
Figure 6: All-India Total Factor Productivity: Sensitivity of Panel Decomposition to Different Assumptions on Exit <!-- Start of picture text --> (a) Without Correcting for False Exit (b) Exit Assigned to Least Productive Firms<br>All−India Total Factor Productivity: Dynamic Decomposition All−India Total Factor Productivity: Dynamic Decomposition<br>Without Correcting for False Exit Assuming Least Productive Firms Exit<br>Year Year<br>Aggregate Average Survivors Aggregate Average Survivors<br>Reallocation Survivors Entrants Reallocation Survivors Entrants<br>Exiters Exiters<br>(c) Exit Assigned to Most Productive Firms<br>All−India Total Factor Productivity: Dynamic Decomposition<br>Assuming Most Productive Firms Exit<br>Year<br>Aggregate Average Survivors<br>Reallocation Survivors Entrants<br>Exiters<br>19851986198719881989199019911992199319941995199619971998199920002001200220032004 19851986198719881989199019911992199319941995199619971998199920002001200220032004<br>19851986198719881989199019911992199319941995199619971998199920002001200220032004<br>1 1<br>.5 .5<br>TFP TFP<br>0 0<br>−.5 −.5<br>1<br>.5<br>TFP<br>0<br>−.5<br><!-- End of picture text --> Total factor productivity (TFP) decompositions for the panel of firms, conducted at the all-India level, using the MP method. “Aggregate” indicates market-share weighted mean productivity, “Average Survivors” and “Reallocation Survivors” indicate unweighted mean productivity and the covariance between market share and productivity for surviving firms, respectively, and “Entrants” and “Exiters” indicate the contributions of entering and exiting firms. In Panel (a), we have not corrected for false exit. In Panels (b), and (c), exit is assigned among the pool of potential exiters by assuming that only the least or most productive firms exit, respectively. All graphs use the same scale to aid in comparison.

41
increasing female education and labor force participation are expected to work against these pressures for son preference in settings where it exists (see for example Chung and Das Gupta 2007). We explore whether there is such a son preference in fertility decisions in the developing world; how it varies across countries and regions; whether it is associated with measures of modernization such as urbanization, female education, and wealth; and the potential consequences of son preference in fertility decisions for household demographic composition and the investment in girls’ human capital.

A handful of empirical studies have investigated how gender preferences in fertility decisions vary during the development process. Hank and Kohler (2000) focus on European countries. Using Fertility and Family Surveys from 17 countries, they find substantial heterogeneity across Europe, with a tendency towards a mild preference for a mixed sex composition. Their data suggest a girl preference in the Czech Republic, Lithuania, and Portugal. Andersson et al. (2006) use historical data from Denmark, Finland, Norway and Sweden to show no effect of gender on fertility for second births, a desire for gender balance at third births and heterogeneity across countries at fourth births (son preference in Finland and daughter preference in the other three countries).

In developing countries, most of the literature has focused on individual Asian countries with a prevalence of discrimination against women.<sup>2</sup> An important exception to these countryspecific studies is Arnold (1992, 1997), who considers the impact of sex-ratios on subsequent fertility behavior across many developing countries. Arnold (1992) shows that the most typical

> 2 For example, Park (1983), Arnold (1985), Bairagi (1987) and Larsen, Chung, and Das Gupta (1998) show the strong impact of son-preference on future fertility in Korea; Arnold, Choe and Roy (1998), Dreze and Murthi (2001) and Jensen (2007) find evidence that son-preference affects demographic behavior in India; Haughton and Haughton (1998) show a similar pattern in Vietnam; while Pong (1994) and Leung (1998) document the pattern among the ethnic Chinese population in Malaysia. One study addresses the issue in Egypt, with a similar finding of sonpreference having impacts on fertility behavior (Yount, Langsten and Hill 2000).

2
Policy ReseaRch WoRking PaPeR 4688

# **Abstract**

Using recent matched employer-employee data from the manufacturing sector in 20 Sub-Saharan African countries, the authors analyze how the supply of skills and legal origin of the country affect the wage setting process. The wage analysis yields three main findings. First, increasing returns to education, especially for older workers, suggest that the expansion of education in Africa has reduced returns to education for entrants in the labor market. Second, age effects matter not just for returns to education, but also for the wage setting process more generally. In particular, in civil-law countries, returns to seniority are rewarded only after a certain age.

Third, workers exercise some power in the wage setting process but their influence varies by linguistic group. In common-law countries, union presence benefits all workers equally, not just members, whereas in civillaw countries, only older members enjoy higher wages. The authors also contrast wage premia with relative marginal productivities for different age, occupation, and education categories. The findings show that in general, older, highly educated, and highly ranked workers receive wage premia that do not reflect a higher relative marginal productivity.

This paper—a product of the Poverty Reduction and Economic Management Department, Africa Region—is part of a larger effort in the department to analyze the relationships between labor market policy, economic growth, and poverty reduction in Sub-Saharan Africa. Policy Research Working Papers are also posted on the Web at http://econ.worldbank. org. The authors may be contacted at lfox@worldbank.org, and aoviedo@worldbank.org.

_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
# VI. References

- Betcherman, G., 2014. Labor Market Regulations: What do we know about their impacts in Developing Countries?. _The World Bank Research Observer,_ pp. 124-153.

- Betcherman, G. & Pages, C., 2009. _Estimating the Impacts of Labor taxes on Employment and the Balances of the Social Insurance Funds in Turkey,_ Washington DC: The World Bank.

- Bourguignon, F. & Spadaro, A., 2006. Microsimulation as a tool for evaluating redistribution policies.. _The Journal of Economic Inequality 4, no. 1 ,_ pp. 77-106.

- Creedy, J. & Duncan, A., 2002. Behavioural Microsimulation with labour Supply Responses. _Journal of Economic Surveys,_ 16(1).

- De Agostini, P. P. A., Sutherland, H. & Tasseva, I., 2014. The effect of tax-benefit changes on the income distribution in EU countries since the beginning of the economic crisis.. _EUROMOD Working Paper,_ Issue No. EM9/14.

- Figari, F., Levy, H. & Sutherland, H., 2007. Using the EU-SILC for policy simulation: prospects, some limitations and suggestions.. _EUROMOD Working Paper Series,_ Issue No. EM1/07.

- Galiani, S. & Weinschelbaum, F., 2012. Modelling Informality Formally: households and firms. _Economic Inquiry,_ Volume 50, pp. 821-838.

- Gimpelson, V. & Kapeliushnikov, R., 2011. Labor market adjustment: Is Russia different?. _Series WPR labour Markets in Transition_ , Issue WP3/2011/04.

- Gimpelson, V. & Kapeliushnikov, R., 2014. Between Light and Shadow: INformality in the Russian Labour Market. _IZA Discussion Paper_ , Issue 8279.

- Immervoll, H. & O‘Donoghue, C., 2009. Towards a multi-purpose framework for tax-benefit microsimulation: lessons from EUROMOD. _International Journal of Micro Simulation, no. 2,_ pp. 43-54.

- Kim, Y. S., Matytsin, M. & Freije, S., forthcoming. _Informal Employment and Worker's Wellbeing in Russia._ s.l.:s.n.

- Kubik, J. D., 2004. The incidence of personal income taxation: evidence from the tax reform act of 1986.. _Journal of Public Economics,_ Volume 88, pp. 1567-1588.

- Lehmann, H., Muravyev, A., Razzolini, T. & Zaiceva, A., 2013. The wage and non-wage costs of displacement in boom times: Evidence from Russia. _Journal of Comparative Economics,_ pp. 1184-1201.

- Lehmann, H. & Zaiceva, A., 2013. Re-defining Informal Employment and Measuring its Determinants: Evidence from Russia. _IZA Discussion Paper Series_ , December, Issue IZA DP No.7844.

- López-Calva, L. F., Lustig, N., Matytsin, M. & Popova, D., 2017. Who Benefits from Fiscal Redistribution in the Russian Federation?. In: _The Distributional Impact of Taxes and Transfers: Evidence From Eight Developing Countries._ Washington, DC: The World Bank, pp. 199-233.

- Lustig, N., 2018. _Commitment to equity handbook. Estimating the impact of fiscal policy on inequality and poverty.._ s.l.:Brookings Institution Press and CEQ Institute, Tulane University..

32
Policy Research Working Paper 9533

# **Abstract**

Refugee camps are believed to represent safe havens for forcibly displaced persons, but studies looking at refugees’ quality of life in camps are few. This paper explores how Syrian refugees’ quality of life in camps in Jordan differs from that of Syrian refugees residing outside camps. Using data from the Syrian Refugee and Host Community Survey, the study measures life quality through indicators of subjective life experience and material living conditions. Data are analyzed using advanced statistical methods (difference-in-difference and propensity score matching) to control for selection bias that could skew estimates of causal effects. The results show that refugees living outside camps enjoy a higher quality of life than those living in camps. Out-of-camp refugees are less likely to live below the national abject poverty line or in overcrowded houses. They possess more household assets, are more satisfied with access to services, and report higher life satisfaction. Refugee camps appear to serve as safe havens for refugees who lack the capability to exit camps, and camps could be redundant for those who possess adequate capabilities and freedom to function in the urban and peri-urban areas.

This paper is a product of the Poverty and Equity Global Practice. 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 author may be contacted at cobi1@worldbank.org.

_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
24 Turning specifically to national authorities, aside from facilitating a supportive business and incentive enviroment for exporting, is their appropriate role in supporting export marketing? One task is to "marke **t** he country" - to raise international awareness of the potential advantages of doing business, including export business, with the emergig export nation.2Q/ What emerges from t'lis study is that a case can also be made to encourage through - partial subsidies - as opposed to directly deliver the use of export marketing supports. Consideration could also be given to using the lure of financial support to encourage the development of decentralized delivery of export marketing senrices - to facilitate the establishment of subsector specific industry associations that are responsive to SME concerns, to encourage those that function primarily as lobbying organizations to develop the capability to provide export marketing and other services to their members, or to encourage the emergence of private providers of export marketing services, including for-profit sponsors of trade fairs. Finally, looking beyond specific collective services, public policy may have some role to play in nurturing the private networks that have emerged in this comparative study as the bedrock of export marketing efforts. Although not studied in any depth, the case studies uncovered tanalizng hints of pr-active goverment efforts to promote such networks: public support for the development of private trading companies in Korea and, earlier, in Japan; Japanese legislation to protect the iterests of smal firms embedded in subcontractng relationships; actions in Korea to designate specific lines of business for subcontracting rather than vertically integrated production. To be sure, as is documented by both the individual case studies and the volrmniinous literatre on the determinants of inter-firm contacting arrangementss,2J/ the development of these networks has largely been the result of spontaneousprivate forces, often deeply rooted in national history and culture. Yet, insofar as incentives can encourage subcontracting or entry by export traders (both large and small) the opporunities 2Q/ For a detailed discussion of how to proceed with this task, see Wells and Wint (1990). 2 L1/ - For one key contrbution, see Williamson (1985). 21. For key co.tn
<!-- Start of picture text --> Evaluation of the number of dwelling units produced per year between 2001 and 2011 per type of land use<br>year 2001 year 2011<br>Average Total<br>Additional |number of |addition<br>Households |built-up Households |number of |units to the<br>built-up area |density orhousing |jarea density orhousing — |units created per |built up<br>Type of use |(km2) (p/ha) population units (km2) (p/ha) population units created year area (ha)<br>Mix Built-up} 121.14 138 1,669,096 370,904 142.51 148 2,104,960 473,038 102,134 10,213 2,137<br>Old City] 5.60 665 372,633 82,806 5.60 750 420,020 94,389 11,583 1,158 -<br>Slums and chalis| 14.92 1,070 1,596,839 354,847 15.29 1,230 1,820,300 422,551 67,704 6,770 36<br>Gamtal| 10.73 700 751,161 166,922 11.69 850 993,485 223,261 56,340 5,634 96<br>Industry 177 50 78,853 17,523 16.69 60 100,161 22,509 4,986 499 92<br>Villas in large estates 17.25 30 51,753 11,500 20.47 35 71,660 16,104 4,603 460 322<br>Total 185.41 244 4,520,335 1,004,501 212.25 262 5,570,585 1,251,852 247,351 24,735 2,684<br>Sources: aggregate population :census data; area per land use type: Google earth image measurements; population per land use type: density measurement<br>File: AB_pop and land use 2000_2011.xIsx<br><!-- End of picture text -->
<!-- Start of picture text -->
- ee ee<br>-ee<br>0.25 a "<br>0.20ee —* Affica<br>= —- Asia<br>7 —*— Europe<br>oe d —>- Lat Am & Carib<br>0.15 —. Le : —- Nerth America<br>2<br>my a aa se<br>0.10pa(be = = ee2 — “ | = —s— Oceania<br>* — —2}.—-—*—*<br>0.05° —- soe + Source: UN, World<br>Populetion<br>Prospects 2006.<br>0.00<br>1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050<br><!-- End of picture text -->
[FIGURE 4: Long–run effects]

# _3.7 Initial conditions of banking systems prior to government interventions_

Figures 1 and 2 indicate the policy responses do not affect all countries equally. To better understand these heterogeneities, we now investigate whether the initial market conditions play a role for these cross-country differences. From a policy perspective, it is useful to understand if the competitive response to interventions varies in a predictive way to aid the actions taken by policymakers.

Demirguc-Kunt and Detragiache (2002), Claessens and Laeven (2004), Martinez Peria and Mody (2004), and Beck, de Jonghe, and Schepens (forthcoming) show that characteristics of banking markets such as structure, contestability, and moral hazard are related to competition. Thus, these characteristics are likely to either amplify or mitigate the effects of policy responses.

We illustrate our arguments about the effect of initial conditions as follows: If blanket guarantees boost competition by giving rise to moral hazard if a country had no deposit insurance before the announcement of blanket guarantees, then the effect of such guarantees should be greater in countries where no deposit insurance scheme was in place. Foreign banks may also play a role because their presence suggests greater contestability. If foreign banks are well represented prior to nationalizations, the competition-increasing effect may be relatively limited. Likewise, if a country does not have a contestable banking system prior to a crisis reflected in activity restrictions and high entry barriers, the competition-enhancing effect of liquidity support is likely to be muted.

We use the HHI to measure market structure (Claessens and Laeven (2004)). Foreign bank penetration, measured by the share of foreign-owned institutions, is our first indicator for contestability. Martinez Peria and Mody (2004) show that foreign banks’ conduct differs from the behavior of domestic banks. Contestability is also reflected in entry barriers and activity restrictions (Claessens and Laeven (2004)). The entry restrictions index summarizes the procedures required to obtain a bank license, the percentage of denied applications for licenses, and the minimum capital required. The index ranges between 0 and 8; it is increasing in restrictions. We capture activity restrictions with the activity restrictions index described in Section 3.4. To approximate moral hazard, we rely on a dummy that takes on the value one if a country has explicit deposit insurance. To calculate initial conditions for concentration, foreign ownership, activity restrictions, and entry restrictions, we take the mean value of these variables in the countries from the treatment group prior to the announcement year of the intervention. For the initial conditions of deposit insurance, we code the variable as one if a country had explicit deposit insurance in place or zero otherwise. Since we need to define the initial conditions also for the control group, we use a _1:n_ matching procedure that finds at 18