rafmacalaba/datause-encoder-data huggingface dataset:
Making creative use of the Adelman-Taft (AM) index of socio-economic development, Temple and Johnson (1998) demonstrate that social capability measured in the 1960s predicted more accurately than conventional indicators which countries would grow in the 1980s. They conclude that over a period of 25 years, a one standard deviation increase in this variable would raise the annual growth rate by 1.8 percentage points. As an illustrative example, if India had achieved the same level of social development on this measure as South Korea by 1960, then its income per capita would have grown at just about three percent a year instead of 1.3 percent. India's income per capita in 1985 would then have been almost 60 percent higher.

These findings have been criticized because the AM index included some economic indicators rather than pure social indicators. For further analysis, Temple and Johnson use four social indicators, to capture underlying social arrangements. They are: kinship (dominance of the immediate family over the extended family or clan and tribal allegiances); modernization of outlook (which included an assessment of social and political participation through voluntary associations and also the support for political and economic modernization); the extent of mass communications (newspaper circulation and number of radios per head); and the importance of an indigenous middle class (proportion of men employed in the professions in contrast to number of expatriates in these professions). They run regressions using these four components.

All the social variables except outlook have statistically significant relations with growth. The relationship between mass communications and growth remains robust even after controlling for a range of human capital, trade policy, political stability and ethnic fragmentation. The authors conclude by suggesting that the extent of mass communication maybe a good proxy for the strength of civic communities, as reflected in trust and membership of associations.

Temple and Johnson (1998) also examine the relationship between measures of trust and associational activity as measured in the World Values Survey and their social indicators. Although the overlap in countries from the two data sets was only 10, the results are suggestive. They find negative or insignificant relations between the two sets of social measures except when they divide up the associational activity measure into groups that are likely to be distributional coalitions (negative correlation) and groups that are Putnamesque (positive correlation).

La Porta and colleagues (1997) once again used the trust data from the World Values Survey to examine the thesis that trust or social capital determines the performance of society's institutions through cross-country regressions. Trust is the propensity to co-operate. They argue that trust is needed more to support co-operation between strangers or between those who 21
inconvenient or assets may be liquidated at inopportune moments (to get ready cash) and all of these may be inefficient. But the impact on health will be small.

How well people can take care of their health problems can depend crucially on the relationship between the timing of symptoms and treatmtent. In emergency situations, to take an extreme case, the effectiveness of treatment is tightly time-bound and there is no chance for shopping around. Demand may be inelastic for treatment but other markets, such as emergency transportation or credit may not work well and public intervention may still be able to increase appropriate service use. This depends on whether pricing or other dimensions of -access which government can influence act as a barrier to care.

A somewhat different dynamic provides another way in which governments may be able to increase access to socially optimal care. For health problems which can be treated if detected early, with symptoms which are relatively minor at early stages and, therefore, for which examinations may be highly elastic with respect to price or accessibility, government subsidies may well increase the appropriate use of services. Some types of cancer screening may fall into this category. Note that this line of reasoning relies on subtle interactions of the severity of symptoms, the effectiveness of treatment and, most importantly, the price (or location) responsiveness of demand for care. In general, however, one would expect more serious illnesses to be associated with more inelastic demand for public services and therefore, less potential influence of government policy on health status. Makinen and Raney (1994) summarize five studies of medical care demand and find that among the consistent results are 33
Growth payoffs will appear as disappointing, despite substantial efforts at reform.

The bottom line is that the balance of forces going forward appears less favorable to rapid structural change than has been the case during the past six decades. We may well need to moderate the optimism that the recent experience of high growth across the developing world has spawned.

# **References**

Acemoglu, D., S. Johnson, and J. Robinson. 2001. “The Colonial Origins of Comparative Development: An Empirical Investigation.” _American Economic Review_ 91 (5): 1369–1401. Aghion, P., and P. Howitt. 1992. “A Model of Growth through Creative Destruction.” _Econometrica_ 60 (2): 323–351.

Androe, G. 1981. _Industry in Ghana. Production Form and Spatial Structure._ Stockholm: Sweden: Scandinavian Institute of African Studies.

Baldwin, R. 2011. _Trade and Industrialisation after Globalisation’s 2nd Unbundling: How Building and Joining a Supply Chain Are Different and Why It Matters._ Working Paper 17716. Cambridge, MA: National Bureau of Economic Research.

Devarajan, S. 2013. “Africa’s Statistical Tragedy.” _The Review of Income and Wealth_ 59 (S1): S9–S15.

de Vries, G. J., M. P. Timmer, and K. de Vries. 2015. “Structural Transformation in Africa: Static Gains, Dynamic Losses.” _Journal of Development Studies_ 51 (6): 674–688.

Diamond, J. 1997. _Guns, Germs, and Steel: The Fates of Human Societies_ . New York: Norton.

Ewusi, Kodwo. 1986. _Statistical Tables on the Economy of Ghana 1950–1985._ Accra: Institute of Statistical, Social and Economic Research, University of Ghana.

Field, A. J. 1978. “Sectoral Shift in Antebellum Massachusetts: A Reconsideration _.” Explorations in Economic History_ 15 (2): 146–171.

Foster, L., J. C. Haltiwanger, and C. J. Krizan. 2001. “Aggregate Productivity Growth. Lessons from Microeconomic Evidence.” In _New Developments in Productivity Analysis,_ edited by C. R. Hulten, E. R. Dean, and M. J. Harper. Chicago: University of Chicago Press.

Glaeser, E. L., R. La Porta, F. Lopez-de-Silanes, and A. Shleifer. 2004. “Do Institutions Cause Growth?” _Journal of Economic Growth_ 9 (3): 271–303.

Gollin, D., D. Lagakos, and Michael E. Waugh. 2014. “The Agricultural Productivity Gap.” _Quarterly Journal of Economics_ 129 (2): 939–993.

Grossman, G., and E. Helpman. 1991. _Innovation and Growth in the Global Economy._ Cambridge, MA: MIT Press.

37
Figure 3: Ricardian and Interest Rate Channels: Joint Model <!-- Start of picture text --> A. Impulse Responses<br>Private Consumption CDS<br>0.3 70<br>60<br>0.2<br>50<br>0.1<br>40<br>0.0 30<br>-0.1 20<br>10<br>-0.2<br>0<br>-0.3<br>-10<br>-0.4 -20<br>Weak fiscal position Strong fiscal position<br>-0.5 -30 Weak fiscal position Strong fiscal position<br>1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20<br>Quarters Quarters<br>B. Multipliers<br>On Impact 2 Years<br>0.6 1.6<br>0.4 1.2<br>0.2 0.8<br>0.0 0.4<br>-0.2 0.0<br>-0.4 -0.4<br>23.1 32.0 38.5 42.8 47.4 54.6 63.8 76.7 23.1 32.0 38.5 42.8 47.4 54.6 63.8 76.7<br>Government debt (percent of GDP) Government debt (percent of GDP)<br><!-- End of picture text --> Note: The upper graphs show the conditional impulse responses (deviation from baseline in percentage points) for strong (blue) and weak (red) fiscal positions. The lower graphs show the fiscal multipliers on impact and after two years (cumulative change in output relative to cumulative change in government consumption after a fiscal shock) by government debt, ranging from the 10<sup>th</sup> to the 90<sup>th</sup> percentile of government debt in the sample. These are based on estimates from the IPVAR model, where model coefficients are conditioned only on fiscal position. Government debt as a percentage of GDP is the measure of fiscal position. The strong fiscal position corresponds to the 10<sup>th</sup> percentile of debt-to-GDP ratio from the sample, while the weak fiscal position corresponds to the 90<sup>th</sup> percentile. Solid lines represent the median, and dotted bands are the 1684 percent confidence bands.

20
Table 10. Heterogeneous Effects by Insurgent Presence

||Post-E|lection|Pre-E|lection|
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|Incumbent victory|0.37<br>|0.21<br>|0.11<br>|0.0024<br>|
||(0.42)|(0.33)|(0.89)|(0.63)|
|Insurgent presence _×_ incumbent victory|0.84**<br>|0.53**<br>|0.22<br>|0.19<br>|
||(0.36)|(0.23)|(0.82)|(0.61)|
|Margin|0.70<br>|7.38<br>|14.8<br>|11.5<br>|
||(17.0)|(15.2)|(22.0)|(13.7)|
|Insurgent presence _×_ Margin|–22.4|–22.7*|–28.3|–17.9|
||(16.8)|(12.8)|(18.4)|(14.9)|
|Margin _×_ incumbent victory|–4.30|–12.5|–32.7|–37.8|
||(19.6)|(15.9)|(39.6)|(30.1)|
|Insurgent presence _×_ Margin _×_ incumbent victory|–19.7|11.6|27.3|29.5|
||(50.3)|(21.6)|(46.4)|(33.9)|
|Mean of dep. var.|0.50|0.50|0.72|0.72|
|Control variables|No|Yes|No|Yes|
|No. of municipalities|153|153|153|153|

_Source:_ Data for the study comes from field reports of the Armed Forces of the Philippines (AFP) and election returns from the Philippines Commission on Elections (COMELEC). _Note:_ The running variable of the RD design is the incumbent margin of victory. All regressions are weighted by a triangular kernel with a bandwidth of 0.05. Reported values are marginal effects, calculated at the sample means. Standard errors are in parentheses. *, ** and *** denote statistical significance at the 10%, 5% and 1% levels. Control variables are the same as in Table 3.

34
<!-- Start of picture text --> =<br>75<br>=<br>oS<br>5 ==(=:<br>=<br>25<br>0 i) 2 4 6 81 10 121 14 16 18 20 22 24<br>Months since start of employment spell<br>—— Control ———-— Treatment<br>95% Cl 95% CI<br><!-- End of picture text --> <!-- Start of picture text --> I<br>75 i --<br>'_,<br>a<br>5 a t_ 1 . a “le<br>a<br>25<br>i) 0 2 4 61 81 10 12 141 16 18 20 22 24<br>Months since start of employment spell<br>—— Control ———- Treatment<br>95% CI 95% CI<br><!-- End of picture text -->
# **1. INTRODUCTION**

The performance of immigrants in the destination labor markets is among the key issues in the migration literature. Successful integration and career performance increase the benefits of migration to both the migrants and the destination countries. On the other hand, migrants’ failures to receive wages or to obtain jobs that are commensurate with their qualifications might lead to social costs and negative public opinions on migration. The stereotypes of immigrant taxi drivers with physics doctorates exist because there is, at least, some anecdotal evidence to support it. The critical questions are how widespread and long lasting these labor market “under-placements” of skilled immigrants are. These issues are the focus of this paper.

There is significant variation among the findings in the literature on immigrants’ performance in the destination labor markets. Some papers find that migrants perform quite well and catch up rapidly with the native workers<sup>1</sup> while others cast doubt whether convergence occurs at all.<sup>2</sup> This paper contributes to this debate by investigating the long-term convergence of labor market performance among male immigrants to the US who come from different countries. We track the same male cohorts in terms of age and arrival dates using data from 1980, 1990 and 2000 Censuses. While controlling for individual attributes and focusing on occupational quality indices as opposed to wages as a measure of assimilation, we answer three closely related questions. First, do the initial occupational placement levels of skilled immigrants differ by country of origin when other factors are taken into account? Second, how does occupational performance by country of origin change over time and, more specifically, do we observe convergence among migrants from vastly different origin countries? Finally, to what extent do country of origin attributes explain these temporal patterns of the occupational placement?

The first finding is that predicted entry-level occupational placement of the tertiary educated immigrants varies widely by country of origin. We observe significant variation even among neighboring countries that have similar economic and social characteristics. Thus narrow comparisons between natives and immigrants, or crude aggregations of migrants into large geographic areas are likely to overlook important variations that have important implications. Second, for the majority of these origin countries, there is evidence of significant improvement in the occupational placement of their migrants over time and a certain degree of convergence among migrants from different countries. In other words, individuals from countries with low initial performance improve faster than those migrants from countries with higher initial

> 1 Chiswick (1978)

> 2 Borjas (1985), Lubotsky (2007), Kim (2009)

2
# **Comparisons with full sample**

# Table A1. 1: PMR

||Product<br>regulation|market|Inward-<br>oriented<br>policies|Outward-<br>oriented policies|
|---|---|---|---|---|
|Australia|0.9||0.9|0.9|
|United Kingdom|0.9||1.2|0.5|
|Iceland|1.0||1.4|0.4|
|United States|1.0||1.2|0.8|
|Ireland|1.1||1.4|0.6|
|Denmark|1.1||1.3|0.9|
|New Zealand|1.1||1.3|0.9|
|Canada|1.2||1.2|1.2|
|Albania|1.2||1.7|0.5|
|Sweden|1.2||1.5|0.9|
|Luxembourg|1.3||1.6|0.8|
|Japan|1.3||1.5|1.0|
|Finland|1.3||1.7|0.8|
|Belgium|1.4||2.0|0.5|
|Netherlands|1.4||1.8|0.8|
|Austria|1.4||1.8|0.8|
|Slovak Republic|1.4||1.3|1.5|
|Germany|1.4||1.9|0.8|
|Norway|1.5||1.9|0.9|
|Korea|1.5||1.7|1.3|
|Portugal|1.6||2.0|0.9|
|Spain|1.6||2.1|0.9|
|Romania|1.6||1.8|1.4|
|Switzerland|1.7||2.1|1.1|
|France|1.7||2.1|1.1|
|Czech Republic|1.7||2.2|1.1|
|Bulgaria|1.8||2.1|1.4|
|Greece|1.8||2.2|1.3|
|Italy|1.9||2.3|1.3|
|Brazil|1.9||1.8|1.9|
|Hungary|2.0||2.4|1.5|
|Croatia|2.0||2.4|1.5|
|Mexico|2.2||2.1|2.3|
|Turkey|2.3||2.6|1.8|
|<br>Poland|2.8||2.9|2.5|

NOTE: The values of indicators refer to 2007 for Albania and Croatia, 2006 for Bulgaria and Romania, 2004 for Brazil, and to 2003 for all other countries (Conway et al. 2005).

33
Policy Research Working Paper 5650

# **Abstract**

This paper quantifies the magnitude of transitions across occupational categories in Colombia, a country with high unemployment and informality but quickly increasing its social security coverage for health. The analysis makes use of a panel of households between 2008 and 2009, representative of the main metropolitan areas in the country. Results confirm previous evidence found in Colombia and elsewhere in the region that transitions between occupations are large and asymmetric: they are disproportionally more likely to happen from formal to informal occupations than _vice versa._ The paper finds for the first time that such transitions are also different for salaried workers compared with the selfemployed, as well as by poverty status of the worker. Salaried workers are more likely to transition first into other salaried jobs, while self-employed are more likely to transition into unemployment or out of the labor force. There are marked differences in the profiles of transitioning and non-transitioning workers, both in terms of socioeconomic characteristics and social security coverage. Causal analysis shows that affiliation to social security on health deters occupational transitions, while pension insurance does not. Hence, high-volume transitions may not be crisis-specific phenomena, but rather associated with contributive and non-contributive social security mechanisms that incentivize informality, and workers’ preferences for informal jobs. The debate on labor market and social security reforms needs to take these features of transitions into account.

This paper is a product of the Poverty Reduction and Equity Unit, Poverty Reduction and Economic Management Network; and the Latin America and Caribbean Social Protection Sector, Human Development Network. 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://econ.worldbank.org. The author may be contacted at jcuesta@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
Table A2. Gender Differences

|||Me|ans|P-value<br>|
|---|---|---|---|---|
||(1)<br>N. Obs|Female<br>(2)|Male<br>(3)|(4)<br>of t-test<br>of (2)-(3)|
|Panel A: Access to Media|||||
|Access to Radio (1=Yes)|1,923|0.47|0.42|0.061|
|Number of hours of radio listened to in an average week|852|9.7|9.63|0.867|
|Access to TV (1=Yes)|1,923|0.67|0.629|0.103|
|Number of hours of TV watched in an average week|1,222|15.3|11.0|0.000|
|Access to cable TV (1=Yes)|1,923|0.29|0.23|0.008|
|Listens to BBC's urdu service for world news(1=Yes)|852|0.10|0.48|0.000|
|Panel B: Knowledge of Political Parties and Elections|||||
|Share of political party signs correctly identified|1,923|0.28|0.42|0.000|
|Share of political party names correctly identified|1,923|0.86|0.96|0.000|
|Knows the gender of main candidates (1=Yes)|1,923|0.95|0.98|0.483|
|Recalls names of main candidates (1=Yes)|1,923|0.82|0.86|0.488|
|Recalls winning candidate (1=Yes)|1,923|0.90|0.95|0.219|
|Aware of EmergencyRule(1=Yes)|1,923|0.10|0.51|0.000|
|Panel C: Participation in Public Life|||||
|Attends community meetings (1=Yes)|1,923|0.18|0.52|0.000|
|Attends demonstrations (1=Yes)|1,923|0.12|0.23|0.000|
|Attended political rally before intervention (1=Yes)|1,923|0.05|0.24|0.000|
|Takes action|||||
|If name missing in voter list (1=Yes)|1,923|0.76|0.92|0.000|
|If police mistakenly arrest family member (1=Yes)|1,923|0.93|0.98|0.000|
|If family land is seized (1=Yes)|1,923|0.92|0.98|0.000|
|Index of community action taken|1,923|-0.29|0.69|0.000|
|Contacts local councilor (1=Yes)|1,923|0.25|0.37|0.000|
|Contacts a local political party official (1=Yes)|1,923<br>,|0.22|0.38|0.000|
|Index of formal authority contact|1,923|-0.10|0.34|0.000|
|Contacts a religious leader (1=Yes)|1,923|0.66|0.49|0.000|
|Contacts a traditional ruler (1=Yes)|1,923|0.45|0.32|0.000|
|Index of informal authoritycontact<br>|1,921<br>|0.12<br>|-0.30<br>|0.000<br>|

~~Note: Data come from follow-up survey. Male refers to head of household while female to their~~ spouse. P-values were calculated from a regressions of each variable on a gender dummy. The regression included village fixed effects and standard errors were clustered at the geographical cluster level.
3 there are a number of other effects. Ihe most important of these is the effect of education on fertility, with educated populations growing more slowly. Productivity is also improved in the ho'lsehold sphere. Educated farmers are more productive. And a higher level of education is associated with a higher standard of health. These effects may then feed back into productivity. A more healthy workforce is more productive. And lower fertility is likely to lead to more healthy children who may learn more at school and be more healthy and more productive as adults.

In the context of developing countries, education is also an important policy vehicle for tackling poverty through stimulating economic growth. The 1980 _World Development Report_ emphasized how important education is in terms of influencing economic growth. In particular it was stressed how human development, a condition directly and indirectly affected by education, can lead to reductions in absolute poverty by promoting growth. Psacharopoulos and Steier (1988) observed this process in Venezuela between 1975 and 1984. Human development encompasses education and training, improvements in health and nutrition, and reductions in fertility rates. This view was reiterated in the _World Development Report,_ 1990 which stated '...there is ample evidence that investing in human capital, especially education, also attacks some of the most important causes of poverty." Streeten (1981) argues that the externalities derived from basic education can be large in developing countries, providing ample justification for expanding resources on primary education. We now proceed to explore the economic consequences of education and its external effects in greater detail.

_2.1_ **_Human_** _Capia and_ **_the Rehtrn_** _to Educaton_ **_i_** _Developing &conomkes_ The Human Capital hypothesis was proposed by Schultz (1963) and Becker (1964) and has been one of the most influential in the area of the economics of education. It postulates that an individual chooses an amount of time to devote to education, based on the expected return and expected cost. This approach is concerned primarily with choice in education and is less relevant to compulsory education'. An individual incurs two types of cost when in education. First, there are the direct costs, such as books, tuition fees, etc., and secondly there are foregone earnings. Human capital models view educational choice as an investment with individuals being concerned about rates of return. If an individual's private rate of return for some level of education X exceeds the rate of interest, then it is sensible for the individual to be educated at least to level _X._ One problem in the context of developing economies is that imperfect capital markets and low 'Although in many countries compulsory education is not enforced, particularly in rural areas where monitoring is difficult.