rafmacalaba/datause-encoder-data huggingface dataset:
The weight given to each province in constructing the synthetic control is based on pre-treatment outcomes. We use the pre-treatment average of the outcome dimension, _Y_ , the unemployment rate, employment rate and the import and export per capita of the province to determine the degree of similarity between control group provinces and the treated provinces, which in turn determines the weight assigned to control provinces. The unemployment and employment rates are included to control for the general economic performance while trade values are added to control for the degree of ’openness’ of the province.<sup>6</sup> The treated unit _i_ = 1 is constructed by taking the mean of the outcome variables in the provinces hosting refugees in 2012 or 2013.

# **5 Data**

We use several data sources for the analysis. The IV estimations use data from years 2011 and 2014 while the DD estimations use data from 2009 to 2014. The numbers of refugees up to 2012 are treated as 0. The refugee data for 2012 and 2013 are obtained from UNHCR’s official weekly statements in December. Data on the number of refugees in 2014 is from Erdo ̆gan (2014), who uses statements released by the Ministry of the Interior to compile his data. All refugee data we use in the analysis is provided at the level of 81 provinces. There were in total 1,6 million refugees by November 2014. Data on the number of new firms and their ownership characteristics and value are provided by the Turkish Chamber of Commerce.<sup>7</sup> Data on total sales and gross profits are obtained from the Turkish Ministry of Science, Industry and Technology. Other economic indicator variables, such as population and unemployment rates, are obtained from Turkish Statistics. Since Syrians usually have guest status rather than resident status during the period of analysis, they are not counted in official statistics such as province population and unemployment rates. Turkey is officially divided into 81 provinces and that is the level of our analysis and variables throughout.

The Chamber of Commerce provides data on the number of new firms and the number of new foreign-owned firms at the provincial level. Enterprises defined as firms do 11
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continuous version of this distribution is unable to adequately represent these cases. This problem appears worse than the common concern that empirical distributions may be overdispersed relative to the Poisson, in which the mean and the variance are equal. Especially in cases where large fractions of a sample are zero trade flows that are retained in the analysis, the continuous Poisson specification appears likely to be seriously mis-specified. The Zero-inflated Poisson estimator developed by Lambert (1992) and applied to the gravity model by Burger, van Oordt and Linders (2009) might be one way to retain the advantages of the Poisson estimator while allowing for substantial numbers of zeros.

On the theoretical front, there have also been major recent developments. HMR (2008) provide a heterogeneous-firm trade model that both allows for frequent and asymmetric patterns of zeros in bilateral trade data and introduces a number-of-firms variable, correlated with the probability of non-zero trade that affects trade volume through a love-of-variety effect. They extend the Heckman model so that the standard gravity explanatory variables determine not only the probability of positive bilateral trade (i.e. the probability that the most productive firm finds it profitable to export to a foreign destination) but also the fraction of firms that are productive enough to enter foreign markets when positive trade occurs. This overcomes an omitted-variable problem different from that created by the limited-dependent feature of the data.

# **III. Intuition on the Econometric Problems Associated with Zero Flows**

Since Tobin’s famous (1958) paper, it has been known that zero values of the dependent variable can create potentially large limited-dependent variable biases in parameter estimates, even in linear models, if the estimator used does not allow for this feature of the data generating process. Heckman (1979) generalized Tobin’s approach to estimation in the presence of this problem, casting it in the context of estimation using samples with nonrandom sample selection. A nonlinear version of Heckman’s formulation of the problem is presented in a two equation context: where xi and zi are vectors of exogenous regressors while β and α are vectors of parameters, and E(uji) = 0, 5
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# **Trade and Migration with Renewable Natural Resources: Out-of-Steady-State Dynamics**<sup>*****</sup>

# **and Maurice Schiff**<sup>**b**</sup> **Ramón López**<sup>**a**</sup>

Keywords: renewable natural resources, depletion, transition dynamics, steady state, trade, migration, capital flows JEL Code: F22, O13, O15, Q17, Q27

* The views presented in this paper are those of the authors and do not necessarily reflect the views of the World Bank, its Executive Directors or the governments they represent.

a. University of Maryland at College Park

- b. World Bank, University of Chile, and IZA (Bonn)
and NFtexperienced simultaneous shocks in different directions , YIt might move countercyclically.

# **References**

Acemoglu, D., S. Naidu, P. Restrepo, and J. A. Robinson. 2019. “Democracy Does Cause Growth.” _Journal of Political Economy_ 127(1): 47-100.

- Aldasoro, I. and T. Ehlers. 2019. “Concentration in Cross-Border Banking.” _BIS_

- _Quarterly Review_ June: 1-11.

- Amaral, P. S., and E. Quintin. 2006. “A Competitive Model of the Informal Sector.” _Journal of Monetary Economics_ 53(7): 1541-1553.

- Amin, M. and C. Okou. 2020. “Casting a Shadow: Productivity of Formal Firms and Informality.” _Review of Development Economics_ 24(4): 1610-1630.

- Amissah, E., S. Bougheas, F. Defever, and R. Falvey. 2021. “Financial System Architecture and the Patterns of International Trade.” _European Economic Review_ 136: 103751.

- Ang, J., and S. Kumar. 2014. “Financial Development and Barriers to the Cross-border Diffusion of Financial Innovation.” _Journal of Banking & Finance_ 39: 43-56.

- Antunes, A. R., and T. Cavalcanti. 2007. “Start Up Costs, Limited Enforcement, and the

-

- Hidden Economy.” _European Economic Review_ 51(1): 203 224.

- Bahadir, B., and N. Valev. 2015. “Financial Development Convergence _.” Journal of_ –

- _Banking & Finance_ 56: 61 71.

- Beck, T., R. Levine and N. Loayza. 2000. “Finance and the Sources of Growth.” _Journal_ –

- _of Financial Economics_ 58: 261 300.

- Beck, T., and R. Levine. 2002. “Industry Growth and Capital Allocation: Does Having a

- Market- or Bank-Based System Matter?” _Journal of Financial Economics_ 64 (2): 147– 80.

- Berrak, B., and N. Valev. 2015. “Financial Development Convergence.” Journal of Banking & Finance 56 (C): 61-71.

- Bittencourt, M., R. Gupta, R., and L., Stander. 2014. “Tax Evasion, Financial Development and Inflation: Theory and Empirical Evidence.” _Journal of Banking and Finance_ 41(1): –

- 194 208.

30
3 effective and sufficient to ensure the sustainability of the pension system. The second part of Section 5 examines more radical reforms consisting of shifting from the current PAYG to a fullyfunded system. Several transition paths and their associated costs are analyzed taking into account the specificity of local conditions. Section 6 provides detailed conclusions.

# **II. Description of the Pension System.**

# 2.1. Types of Pensions.

The Ukraine Pension system is similar to public pension schemes in many industrialized countries (World Bank, 1993). It is based on the pay-as-you-go (PAYG) principle. Workers and their employers make contributions to the program over their active careers. These contributions finance benefits to current pensioners. The present employer contribution rate is 32.56 percent of workers' salaries; employees contribute 1 percent of their wages. The pension system currently offers five types of pensions to more than 14 million beneficiaries (Kane 1996):

**Old age pension.** Men over the age of 60 and women over 55 are eligible to receive an old age pension. For the full standard pension, men must have worked for 25 years, and women 20 years, in covered employment. The level of a standard old age pension equals 55 percent of reference earnings (an index of 5 peak years of earnings), plus 1 percent for each year over the minimum standard pension employment years. The normal ceiling of a standard pension is 3 times the minimum pension. People who have not worked long enough to earn a standard pension but have reached the retirement age are eligible for a partial pension. The level of a partial pension depends on the number of employment years but is no less than 50 percent of minimum old age pension. The old age pension program is by far the most important since it benefits about 80 percent of all pensioners (about 11 million individuals).

**Invalidity pension.** This type of pension is available for those who are injured or too sick to work (that is, about 10 percent of all pensioners, or about 1.4 million individuals). Depending on the invalidity category and the number of years of covered employment, the pension level can vary from half the minimum wage to 3 times the minimum wage.

**Survivor's pension.** This pension is available for the spouse or minor children of deceased workers (currently about 800 thousand beneficiaries). Survivor's pensions are in general lower than old-age or invalidity pensions. The average survivor's pension is only about two-thirds of the average old-age pension. For minor children the maximum eligible age of receiving the survivor's pension is 18.

**Social pension.** This pension is for those who have not worked in covered employment but who meet certain conditions, such as being over the normal retirement age or disabled from birth. As social pensions are made available to those who are not contributing to the fund they
# **TABLE 12. HEALTH CARE DELIVERY OBJECTIVES AND PERFORMANCE** **<u>INCENTIVES PROVIDED BY ALTERNATIVE HOSPITAL PAYMENT SYSTEMS</u>**

|||<br>**P**|<br>**ayment syst**|<br>**em objectives**|<br>||
|---|---|---|---|---|---|---|
|**Payment**<br>**mechanism**|**Definition**|**Equity across**<br>**patients**|**Delivery**<br>**efficiency**|**Patient**<br>**satisfaction**|**Cost**<br>**containment**|**Comment**|
|**Global budget**|Fixed annual<br>amount with<br>flexibility in<br>allocations|+|+|+|++++|No incentives for<br>efficiency but ceiling<br>on spending|
|**Line item**<br>**budget**|Fixed annual<br>amount with<br>predetermined<br>allocations|+|-|-|++++|Similar to global<br>budget but more<br>restrictive; prevents<br>management<br>discretion|
|**Per-diem**|Facility paid a<br>daily rate|++|+|++|-|Encourages long<br>lengths of stay|
|**Capitation**|Fixed fee paid<br>per patient|+|-|-|+++|All patients and<br>illnesses reimbursed<br>equally|
|**Prospective**<br>**payments**<br>**(eg. DRG)**|Payment based<br>on charges for<br>“bundled”<br>services<br>determined by<br>diagnosis|++++|+++|+|+++|Promotes efficiency<br>thorugh lump sum<br>payments for all<br>services and cost<br>containment|
|**Fee-for-service**|Facility sets<br>prices and<br>charges<br>(patients) for<br>each service|-|++|++++|-|Providers have<br>incentive to provide<br>unnecessary<br>services to please<br>patients|

Note: Scale is – to ++++. Source: Authors based on Lagenbrunner and Wiley (2002).

The value of prospective payments systems as a tool for improving performance is probably best illustrated by the fact that some form of it is used across the OECD countries; one of the few commonalities across those countries in health care. While often complex, simplified forms of prospective payments have been effectively adopted by Brazil , Chile, and some Eastern European countries, and the results suggest that financial incentives can alter behavior and raise performance in developing and transition countries. Although the approach is not always viable, it nonetheless points to the importance of payments systems in providing effective incentives. The strong incentives and the opportunity for accountability are built into prospective payment systems, partly because they must track performance and spending, suggest that prospective payments should be part of the dialogue on health systems and on reform measures since they can help raise performance and lower (or at least help contain) costs.

45
**Exhibit 13: Growth in Registrations (all companies excluding re‐registrations) by Subsector**

|**2006 – 2012**|**CAGR**|**Contribution to Sector**<br>**Growth**|**Standard**<br>**Deviation**|
|---|---|---|---|
||(i)|(ii)|(iii)|
|**_AGRICULTURE_**||||
|**Crop and animal products**|0.48|0.85|0.38|
|**Forestry**|‐|0.07|0.94|
|**Fishing**|‐|0.02|0.78|
|**Multiple – agriculture**|‐|0.07|1.87|
|**Total – agriculture**|0.52|1.00|0.33|
|**_INDUSTRY_**||||
|**Mining, quarrying**|0.69|0.14|0.89|
|**Manufacturing**|0.46|0.28|0.28|
|**Electricity gas and water**|0.65|0.03|0.55|
|**Construction**|0.37|0.49|0.16|
|**Multiple – industry**|0.43|0.06|0.22|
|**Total industry**|0.42|1.00|0.24|
|**_SERVICES _**||||
|**Wholesale and retail trade**|0.41|0.55|0.27|
|**Hotels and restaurants**|0.43|0.05|0.25|
|**Transport, storage, and**<br>**communications**|0.50|0.08|0.22|
|**Finance, insurance**|0.39|0.04|0.61|
|**Real estate, business services**|0.52|0.11|0.25|
|**Education and health**|0.56|0.02|0.53|
|**Other personal services**|0.67|0.03|0.41|
|**Multiple – services**|0.50|0.12|0.21|
|**Total ‐ services**|0.44|1.00|0.24|

_<u>Note:</u>_ The chart shows:

- (i) The Compound Annual Growth Rate (CAGR) in the number of registered companies, by subsector, between 2006 and 2012.

- (ii) The contribution of newly registered companies to growth in the total number of registrations, by subsector.

- (iii) The standard deviation of the year‐on‐year growth over the period. A large standard deviation indicates volatile growth in the sector.

All companies except re‐registrations are included.

18
Table 6 displays the level of motorization, along with per capita GDP, in the Asian countries considered in this study. The level of motorization in developing Asian countries lags well behind those in developed countries, but since economic growth and energy-demand (and CO2 emissions) growth are linked, the expected expansion of developing Asian economies at an average rate of more than 5 percent per year through 2030, with China, India, Indonesia and Malaysia leading the way, means that the current levels of motorization are likely only a fraction of what they will be in two or three decades as these populous and rapidly growing economies go through a phase of rapid motorization (ADB, 2006). The demand for passenger cars in Asia is growing much faster than per capita income in every country considered other than Bangladesh; sometimes astonishingly so, as in the case of China, Korea and Mongolia. Recent motorization data for Vietnam is not available.

**Table 6: Motorization (Number of passenger cars per 1,000 persons) and Gross Domestic Product per Capita (US$)**

||199<br>|0<br>|200<br>|5<br>|Average<br>Growt <br>|Annual<br>h Rate<br>|
|---|---|---|---|---|---|---|
||Cars per<br>1,000<br>people|GDP per<br>capita|Cars per<br>1,000<br>people|GDP per<br>capita|Cars per<br>1,000<br>people|GDP per<br>capita|
|Bangladesh|0.4|282|0.6<sup>a</sup><br>|422|2.9%|2.9%|
|India|3.2|381|8.0<sup>b</sup>|713|7.4%|4.2%|
|Pakistan|5.0|506|7.7<sup>b</sup><br>|820|3.4%|1.7%|
|Sri Lanka|9.8|479|21.8<sup>b</sup>|1,253|6.4%|3.7%|
|Indonesia|7.2|685|24.7<br>|1,244|8.5%|2.9%|
|Malaysia|96.1|2,432|225.1<sup>b</sup><br>|5,098|6.8%|3.8%|
|Philippines|24.1|724|49.8<sup>b</sup>|1,163|5.7%|1.4%|
|Thailand|21.8|1,572|46.7<sup>a</sup>|2,797|5.6%|3.5%|
|Vietnam|0.5|98|n.a.|621|n.a.|5.9%|
|China|1.4|358|13.4<sup>a</sup>|1,766|17.4%|9.1%|
|Korea|48.4|6,153|222.9<sup>a</sup>|16,454|11.5%|4.7%|
|Mongolia|3.6|567|30.4<sup>a</sup>|800|16.5%|0.2%|

Source: ESCAP (2007b); UN Statistics Division (2008b) Note:<sup>a</sup> data are for 2004;<sup>b</sup> data are for 2003 23
# <mark>WPS3575</mark>

## **THE KIN SYSTEM AS A POVERTY TRAP?**

**KARLA HOFF** and **ARIJIT SEN**<sup>*****</sup>

World Bank Policy Research Working Paper 3575, April 2005 _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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

* We thank Maitreesh Ghatak, Vijayendra Rao, an anonymous referee, and workshop participants at Cornell University, the Santa Fe Institute, and the World Bank for helpful comments. The paper is forthcoming in: _Poverty Traps,_ eds., Samuel Bowles, Steven Durlauf, and Karla Hoff, Princeton University Press, 2006.

1
wage, but increase the labor force participation rate. This evidence contradicts both the collateral and insecure property rights mechanisms.

We use a historical quasi experiment in land policy in Sri Lanka to estimate the effects of land market restrictions on the local labor market. The IV estimates that exploit the historical natural experiment show that the effect of land restrictions on women’s labor force participation is numerically substantial and statistically significant at the 1 percent level. According to the IV estimates, when the land restrictions increase by 1 percentage point (starting from a mean level of restrictions), it increases women’s labor force participation by close to 2.3 percent. The corresponding estimate is 1.7 percent reduction in the wage for women. The results also suggest a greater burden of land market restriction on older women, and a much lower effect on men. To the best of our knowledge, the theoretical and empirical analysis presented in this paper is the first attempt in the economics literature to understand the effects of land market restrictions on women’s labor force participation and wage in rural areas of a developing country.

# References

Acemoglu, D and Simon Johnson and James A. Robinson, 2001. “The Colonial Origins of Comparative Development: An Empirical Investigation”, _American Economic Review_ , American Economic Association, vol. 91(5), pages 1369-1401, December.

Besley, T (1995): “Property Rights and Investment Incentives: Theory and Evidence from Ghana.” _Journal of Political Economy_ , 103, 5, 1995: 903-937.

Briet, O. J. T, P. Vounatsou, D. M. Gunawardena, G. Galappaththy, P. Amerasinghe (2008), “Temporal Correlation Between Malaria and Rainfall in Sri Lanka”, _Malaria Journal_ , May 2008.

Chowdhury, Mohammad Tarequl H., Bhattacharya, Prasad Sankar, Mallick, Debdulal, and Ulubasoglu, Mehmet Ali, 2014. “An empirical inquiry into the role of sectoral diversification in exchange rate regime choice, _European Economic Review_ , Elsevier, vol. 67(C), pages 210-227.

Clemesha, W (1934), “Brief Account of the Natural History of Malaria in Ceylon”, _Ceylon Journal of Science_ , 1934, 3: 157-172.

De Silva, K. M. (1981), _A History of Sri Lanka_ , London, C. Hurst Publisher.

27
Focusing on the low and middle-income country group, table 4 compares the evolution of functional expenditures for fiscal events followed by a growth event compared with those not followed by growth events. In particular, we look at the underlying changes of discretionary public expenditures by function.

Table 4: Characteristics of Fiscal Events in Developing countries According to Their Timing with Growth Events<sup>_a/_</sup>

||fiscal e<br>g|vent follow<br>rowtheve<br>14/63|ed by a<br>nt|fiscal eve<br>a|nt NOT fo<br>growtheve<br>49/63|llowed by<br>nt|
|---|---|---|---|---|---|---|
||Avera<br>Pre-event<br>(1)|ge level<br>Post-event<br>(2)|change<br>ppa<br>(3)<br>=(2)-(1)|Avera<br>Pre-event<br>(4)|ge level<br>Post-event<br>(5)|change<br>ppa<br>(6)<br>=(5)-(4)|
|% of public expenditure in GDP|25.4*|24.0*|-1.4|23.0*|21.7*|-1.3|
|% ofpublic deficitinGDP|-3.4|-0.3*|3.2*|-3.4|-1.2*|2.3*|
|Expenditures by function<br>(in % of total public exp.)|||change<br>%<br>=(2-1)/(1)|||change<br>%<br>=(5-4)/(4)|
|_Education_|12.8|14.4|13%|14.1|15.3|9%|
|_Health_|8.4*|8.8*|5%|5.7*|6.2*|8%|
|_Transport and Communication_|6.4|6.6*|3%*|6.3|5.8*|-7%*|
|_General (non interest) public services_|16.5*|15.4*|-7%*|21.3*|19.3*|-10%*|
|_Defense_|6.0*|5.5*|-8%*|11.7*|10.0*|-14%*|
|_Housing and community amenities_|4.5*|4.2|-7%*|2.7*|3.9|43%*|
|_Recreation, culture, and religion_|1.5|1.0|-30%|1.7|1.4|-13%|
|_Others (residual)_|43.9|44.1|0%|36.5|38.0|4%|

# Notes

Developing countries are defined as low and middle income countries, see Annex A.1.3.

* Test of difference in mean between fiscal event NOT followed by a growth event compared to fiscal event followed by a growth event (i.e. col. 4, 5, 6 compared to col. 1, 2 and 3 respectively). An asterisk indicates significance at 5% level.

a/ Based on the benchmark set of parameters, see table A.4, row 2.

_Source: Authors’ computation from GFS and PWT 6.2 data, see Annex A.2._ 19
seasonality problems the conclusion would be that urban unemployment may have increased from a level of about 3 percent in 1967-69 to 11-15 percent in 1982-85 with a tendency to increase within both of these periods.

For rural areas explicit labor force surveys have only been conducted for 1973-74 and seasonality is a major problem. These surveys were conducted in June, October, and April, in this order, and thus do not cover the winter season where there may be little field work in agriculture and construction work may be down in parts of the country but, on the other hand, farm families may not be looking for employment outside the own farm and in any case unemployment is not easy to either define or measure.

A detailed study by FAO and Turkish authorities gives a picture of agricultural seasonalities in the aggregate. The study is clearly of the "normative" type, "combining labor requirements for each major agricultural operation under different methods (power sources) of production to estimate labor force demand and supply in agriculture" and gave the results shown in Table 1.5. "Peak season surplus" is apparently something conceptually different from "seasonally removable labor surplus", the former estimated to be 990,000 in 1967 and 113,000 in 1972, the latter zero in both years. The peak season surplus for 1967 is identical with that appearing for 1967 in the SPO estimates of national labor force and employment for the period 1962-72. For 1972, however,

-6-