rafmacalaba/datause-encoder-data huggingface dataset:
performance. Third, the extent of convergence weakens over time; the rate of improvement experienced by a cohort declines within the second decade. The fourth finding is that country specific attributes impact on the improvement in immigrants’ occupational performance occurs mainly through their effect on initial placement: thus, they lose significance when initial occupational levels are controlled for in the estimation.

Most papers in the literature focus on wages to assess performance, assimilation and convergence in destination labor markets. In this paper, we use measures of occupational placements instead of earnings because the former are less likely to vary by city or state within the US. This is a significant advantage when measuring performance of people spread over a large geographic area where costs of living and other local factors strongly influence wages. For example, the wages in metropolitan areas like new York City and San Francisco for medium skilled occupations tend to be higher than wages of high skilled occupations in more sparsely populated areas. In addition, characteristics of occupations are less likely to be volatile relative to wages as labor market conditions change over time. In short, biases due to geographic and time effects are less of a concern when occupational placement indices are used as measures of performance.

One main concern is that the magnitude and patterns of return migration can potentially bias the results in this paper. Although prior literature acknowledged this problem and some researchers made inferences about the nature of the selectivity in return decisions, the bias stemming from out-migration is typically left unresolved in studies that rely exclusively on census data. We evaluate to what extent attrition of cohort size due to return migration affects the samples by country. We conclude that estimates are not significantly affected by patterns in return migration. Furthermore, working with data from several Censuses raises serious methodological concerns because the samples are based on responses of different individuals. To check whether results change significantly when correcting for the potential biases, we rerun the individual-level regressions using pseudo-panel techniques. The patterns are robust to these methodological changes.

Occupational status has important implications for understanding economic and social costs and benefits of migration. In the US, there is continuous media coverage about skilled immigrants from certain countries being employed in low skilled jobs while similarly educated immigrants from other countries climbing career ladders very rapidly. Research focusing on occupational mobility of immigrants could provide rigorous grounds for such observations. More importantly, analysis could identify the barriers that prevent migrants from obtaining jobs suitable for their education levels and how those barriers could be removed. It is possible that the under3
quality consultants. Obviously the trade-off was that this led to a small cross-sectional sample size. We discuss the estimation issues this generates in section III.D below.

<u>Treatment and control plants: The 17 firms in our sample had 28 plants. Due to</u> manpower constraints we could collect detailed performance data from only 20 plants, so we designated 20 plants as “experimental” plants and randomly picked 6 control plants and 14 treatment plants. As Table 1 shows, the treatment and control firms were not statistically different across any of the characteristics we could observe.<sup>13</sup> The remaining 8 plants were then the “non-experimental plants”: 3 in control firms and 5 in treatment firms. These nonexperimental plants did not themselves receive consulting services, but data on their management practices and organizational and IT outcomes were collected in bi-monthly visits.

<u>Timing: The consulting intervention was executed in three waves because of the capacity</u> constraint of the six-person consulting team. The first wave started in September 2008 with 4 treatment plants. In April 2009 a second wave of 10 treatment plants was initiated, and in July 2009 the diagnostic phase for the 6 control plants was carried out. Firm records usually allowed us to collect data going back to a common starting point of April 2008.

We started with a small first wave because we expected the intervention process to get easier over time due to accumulated experience. The second wave included all the remaining treatment firms because: (i) the consulting interventions take time to affect performance and we wanted the longest time-window to observe the treatment firms; and (ii) we could not mix the treatment and control firms across implementation waves.<sup>14</sup> The third wave contained the control firms. We picked more treatment than control plants because the staggered initiation of the interventions meant the different treatment groups provided some cross identification for each other, and because we believed the treatment plants would be more useful for understanding why firms had not adopted management practices before.

# **_III.D. Small sample size_**

The focus on large firms meant we had to work with a small sample of firms. This raises three broad issues. A first potential concern is whether the sample size is too small to identify

> 13 Treatment and control plants were never in the same firms. The 6 control plants were randomly selected first, and then the 14 treatment firms randomly selected from the remaining 11 firms which did not have a control plant. 14 Each wave had a one-day kick-off meeting involving presentations from senior partners from the consulting firm. This helped impress the firms with the expertise of the consulting firm and highlighted the potential for performance improvements. Since this meeting involved a project outline, and we did not tell firms about the existence of treatment and control groups, we could not mix the groups in the meetings.

10
# **A.4 Rolling Unconditional Correlations**

Following Tang and Xiong (2012), we normalize the regular monthly commodity price returns by _rm,t−rm_ their respective averages and standard deviations, _rm,t_<sup>_∗_=</sup> <u>�</u> _Tt_ <u>=1</u><sup><u>(</u></sup><sup>_rm,t−_</sup> _<u>rm</u>_ <u>)</u><sup>2</sup> . We then regress the ~~<u>�</u>~~ _T −_ 1 normalized return of commodity _x_ , _rx,t_<sup>_∗_,ontothenormalizedreturnofcommodity</sup><sup>_z_,</sup><sup>_r_</sup> _z,t_<sup>_∗_,with</sup> _x, z_ = 1 _,_ 2 _, ..., M_ and _x_ = _z_ .<sup>�</sup> _ρ_ � _xz_ obtained from the regression _rx,t_<sup>_∗_=</sup><sup>_μ_+ �</sup><sup>_ρxzr_</sup> _z,t_<sup>_∗_+</sup><sup>_ηt_is the estimated</sup> unconditional correlation between the two commodity price returns. We assess the time-variation in the correlation coefficients between all pairs of commodity price returns by estimating rolling regressions with fixed windows of size equal to two and five years – i.e., 24 and 60 months. NeweyWest standard errors, based on a Bartlett kernel and a fixed bandwidth, correct for autocorrelation in the regression residuals and are used to derive reliable rolling 95% confidence intervals for _ρ_ � _xz_ .

26
WPS3448

# **What Are the Right Institutions in a Globalizing World?**

_And.... can we keep them if we’ve found them?_

# Roumeen Islam<sup>1</sup>

## **Abstract:**

Greater trade integration has often been viewed as requiring greater standardization in institutions, without which the benefits of trade do not materialize. There are many current debates concerning the degree and area of standardization needed and these debates are likely to continue for the foreseeable future. This paper, drawing on both the fiscal federalism and the trade literature, argues that increasing trade integration is consistent with a wide array of institutional choices. The final outcome, in terms of which institutions have prevailed, has depended substantially on political pressures for standardization and not necessarily on a clear assessment of economic gains.

## World Bank Policy Research Working Paper 3448, November 2004

_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._

> 1 I would like to thank Marc Bacchetta, William Easterly, and Bernard Hoekman for their comments and suggestions. Thanks are due to Theodora Galabova and Chunfang Yang for their research assistance. All errors are my own. Author details: Room J4-151, World Bank, 1818 H Street, NW. Washington, D.C., 20433. Tel: 202-473-2628. Fax: 202- 676- 9810
6

# **2 Access to ART and Risky Sexual Behavior**

When people become aware of ART, they may adjust their sexual behavior to account for the decline in the costliness of the new treatable disease. Such a response may create a compensation effect that partially reduces the benefits of expanded treatment. Such possible offsetting behaviors have been discussed in the economic literature in the context of other safety (e.g. Peltzman, 1975) and health issues (e.g. Oza, 2009)<sup>7</sup> .

We assume that individuals derive utility from both safe sex and risky sex (e.g. unprotected sex with non co-residing partner). Moreover, the marginal utility of risky sex is greater than that of safe sex<sup>8</sup> . The cost of risky sex is, however, higher than that of safe sex. In particular the cost of risky sex includes the probability of contracting HIV and the ensuing disutility from developing AIDS (this includes the physical pain after the individual develops AIDS, the monetary costs from lost earnings, stigma, premature death, etc.)<sup>9</sup> . The cost of safe sex is kept lower because it does not include all the risks and costs associated with contracting HIV. If the consumer is maximizing her utility subject to a budget constraint, standard economic reasoning implies that at the optimum, the ratio of the marginal utility

> 7A long debated issue is the introduction of seat belts in cars in the US. For instance, Lave and Weber (1970) and Peltzman (1975) argued that seat belt use might produce careless driving and in turn greater risks for non-occupants. As a result, mandatory seat belt laws might increase total fatalities rather than reduce them. However, empirical analyses focusing on the safety regulation of motorized vehicles have generated mixed results. For instance, Cohen and Einav (2003) found that while seat belts usage has a small negative effect on traffic fatalities, there is no evidence suggesting that seat belts usage increases reckless driving. In contrast, using data from recreational boats, McCarthy and Talley (1999) found that the passenger was less likely to wear a personal floatation device (PFD) when the driver had received a formal training. Oza (2009) hypothesizes that the introduction of over-the-counter access to the “morning after pill” lowered the risk of unintended pregnancies, but also lowered the opportunity costs of unprotected sex. She shows that for women who were exposed to the policy, abortion rates decreased while STIs increased, corroborating disinhibition behaviors.

> 8For example, Rao, Gupta, Lokshin, and Jana (2003) found that prostitutes in Calcutta, India who agree to condom-free sex are paid more, implying that clients derive more satisfaction from condom-free sex. Gertler, Shah, and Bertozzi (2005) found similar results using data from the states of Morelos and Michoacan in Mexico.

> 9We abstract from other sexually transmitted diseases and birth control.
**Polac,Pnning, and Research**

# **World Devolopmenl Reportn**

The Bank is paying increasing, though stil unsystematic, attention to the institutional dimension of public expenditure management. This implies analysis of the processes and procedures by which programs are put together with an assessment of the strengths and weaknesses of the institutions involved and the links between them. Advising governments on these aspects requires more expertise than most Bank staff members possess. The Bank should develop staff skills in this area through:

- Better coordination in the Bank of public expenditure reform issues.

* More intensive, systematic staff training, and more contact with academics and other outside experts through such vehicles as seminars.

* Closer collaboration and more systematic exchange of views between operational staff and the Policy, Planning, and Research complex, including incorporation of feedback from the seminars held by the Economic Development Institute.

* A closer working relationship with the IMF, especially the Fiscal Affairs Department.

* Development of a well-designed program of operationally oriented, detailed case studies of specific country experiences tsuccesses and failures) from which to draw lessons for future operations and country and economic sector work.

Addressing these issues may also have implications for the type of lending instrument the Bank uses. Reforms of public spending are usually dealt with through structural adjustment loans, backed up by technical assistance operations - but these may not always be suitable. If major policy decisions are required to bring about important long-term structu l' changes, a broader, more flexible lending instrume-.: may be more appropriate.

One approach being explored is to fimance a time slice of the country's public investment program (either on a sector-by-sector or aggregate basis, depending on the scope of the reforms to be introduced) to support not only more appropriate programs but also institutional and procedural reforms of the ways in which public expenditures are prepared and implemented. This approach could combine quick-disbursing balance of payments support with the longerterm approach needed to encourage institutional reform.

This is a background paper for the 1988 World Development Report. Copies are available free from the World Bank, 1818 H Street NW, Washington DC, 20433. Please contact Lupita Matthiesen, room S13-067, extension 33757.

The PPR Woiking Paper Series disseminates the findings of work under way in the Bank's Policy, Planning, and Research Complex. An objective of the series is to get these findings out quickly, even if prcsentations are less than fully polished. The findings, interpretations, and conclusions in these papers do not necessarily represent official policy of the Bank.

Produced at the PPR Dissemination Center
|Variable|Mean|SD|p(10)|p(25)|p(50)|p(75)|p(90)|
|---|---|---|---|---|---|---|---|
|Number ofemployees (RUSLANA)|83.3|57.2|28|36|64|115|174|
|Firm age in years|21.7|23.7|4|9|14|22|57|
|Exporter status (dummy)|28.0%|44.9%|0|0|0|1|1|
|Supplier toforeign firm (dummy)|6.5%|24.7%|(0)|0|(0)|(e)|(0)|
|More than 50% privately owned (dummy)|94.7%|22.4%|1|1|1|1|1|
|More than 50% foreign owned (dummy)|2.8%|16.4%|0|0|0|0|0|
|More than 50% state owned (dummy)|2.6%|15.8%|0|0|0|0|0|
|More than 80% ofmanagers with higher degree (dummy)|67.7%|46.8%|0|0|1|1|1|
|More than 20% of non-managers with higher degree (dummy)|39.2%|48.8%|0|0|0|1|1|
|Sales per worker, in thousand USD (2016)|62.5|130|5.2|14.5|32.8|60.8|117|
|Fixed assets perworker, in thousand USD (2016)|19.8|98.2|(0)|0.7|3.1|10.7|33|
|Value added per worker, in thousand USD (2016)|8|13.7|2.5|4.3|5.9|9.1|16|
|TFP index|6.6|5.2|3.8|45|5.7|7.3|9.5|
|Profitmargin,in%|0.70%|35.90%|-7.50%|0.20%|2.80%|7.60%|13.90%|
how drought shocks are distributed among groups of workers with different skills and functions. Since agriculture is a sector that traditionally employs low-skilled labor, based on theory and previous empirical evidence, we can hypothesize that low-skill workers will have a greater chance of being reallocated to sectors with similar characteristics. Conversely, we do not expect significant and wide-ranging effects on workers with higher levels of education and therefore more complex skills. The results presented in Figure 18 appear to be fully in line with our predictions. The impact of drought shocks is concentrated mainly on workers with the lowest levels of education, where we observe a decline in employment of approximately 11 p.p. in the year of the shock, and simultaneously, an absorption of an equal magnitude only in the manufacturing and construction sectors. Importantly, we do not observe significant increases in the unemployment rate. Once again, the duration of the impact is concentrated within just two years, and subsequently, it is completely absorbed. The effects we find on workers with higher levels of education are lower than the low education group.

## **_Effects in urban and rural areas_**

Finally, we present the results obtained by differentiating the sample between workers in urban areas and rural areas. This distinction is important because a large part of climate shocks affects the agriculture sector, which is geographically concentrated in rural areas. Figure 19 confirms that the impacts on the agriculture sector are significant and economically meaningful only in rural areas. However, it is important to note that the labor market dynamics in urban areas highlight a slight decrease in the other sectors and an increase in the unemployment rates.

# **7. Discussion and conclusions**

In this paper we explore the impact of severe drought shocks in the labor market of Tunisia during the period 2000-2019. Tunisia is an important MENA country that is considered a climate hotspot and for which little evidence is available. Importantly, Tunisia is a good case study to investigate the interacted effects of climate change on the local labor markets in a socioeconomic context characterized by a narrow demographic window, a labor force participation rate higher than the average in the Middle East and North Africa region, and regionally clustered economic activities and employment opportunities. We align nationally representative labor force surveys and weather data that allow to calculate SPEI, a 12
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<!-- Start of picture text --> Public education (Tertiary)<br>e<br>90<br>e<br>gee?<br>= 807 @e ee e<br>Pd 70 e e Se e<br>8 e é . : e<br>3 60 =<br>a<br>& e e<br>50 . °<br>40 e<br>0 10 20 30 40 50<br>Unofficial payments needed (per cent of usually/always)<br><!-- End of picture text --> <!-- Start of picture text --> 80 > Unemployment benefits<br>:<br>oo<br>= 60 e?<br>oo8 7 & °<br>s2e° °<br>8407 "e ee? .<br>33 . e ° ,<br>” 20<br>e e<br>fe) e<br>0 10 20 30<br>Unofficial payments needed (per cent of usually/always)<br><!-- End of picture text --> <!-- Start of picture text --> Official documents<br>905 ¢@e<br>e<br>a 80 3, e hd<br>5 hd ee e<br>S °<br>8 70 *' e<br>8 e<br>> 60 e ©<br>® 50 = : °<br>e e<br>40<br>e<br>0 10 20 30 40<br>Unofficial payments needed (per cent of usually/always)<br><!-- End of picture text --> <!-- Start of picture text --> Public education (Primary/Secondary)<br>90<br>°°<br>s e<br>= 80 é e<br>5S- ee e e<br>rs eo oe e<br>g 70) @ 8<br>B °<br>3 s |°<br>o 60<br>50 e<br>0 10 20 30 40<br>Unofficial payments needed (per cent of usually/always)<br><!-- End of picture text -->

<!-- Start of picture text --> Public health system<br>90<br>ee?<br>e<br>80 ° e<br>es °<br>s3 70 : e e .<br>8 e e . e .<br>B ° ee ° °<br>S e e e<br>& ° e e<br>50<br>e ee<br>40 e<br>0 10 20 30 40 50<br>Unofficial payments needed (per cent of usually/always)<br><!-- End of picture text --> <!-- Start of picture text --> 80 Other social security benefits<br>v<br>e<br>= °<br>oo8 60 °e e °<br>s28 e ee >% . .<br>3 e oe °<br>a e<br>co e 6% e<br>20<br>0 10 20 30<br>Unofficial payments needed (per cent of usually/always)<br><!-- End of picture text -->
**PRIVA2Z SAVING IX mExICO, 1580-90**

# Contents

|1. Motivation and Summary|p.3|
|---|---|
|2. Methodological Issues and Measurement Problems|p.5|
|2.1 Methodological Issues|p.5|
|2.2 Measurement Problems|p.6|
|2.2.1 Balance of Payments Data<br>2.2.2 Fiscal Data<br>2.2.3 National Accounts Data|p.6<br>p.9<br>p.10|
|2.3 Durable Consumption|p.11|
|2.4 Data|p.12|
|3. Private Saving Performance, 1980-90|p.13|
|3.1 Saving Rates in Mexico, 1980-90|p.<sup>1 3</sup>|
|3.2 Comparison with the Conventional Measure of Private Saving|p.19|
|3.3 Disaggregation of Consumption Expenditures|p.20|
|3.4 Dissagregation of Disposable Income|p.21|
|References|p.22|

Annex A: A Revision of National Accounting Procedures in Mexico Annex B: Statistical Annex Annex C: Quarterly and Monthly Consumption Series in Mexico We have bonefitted from comments by Klaus Schmidt-Hebbel and Sweder van Wijabergen. We are very grateful to officials from the Government of Mexico for facilitating the data of this study and for helpful discussions. Heinz Rudulph and Rebecca Brideau provided able research assistance.
<!-- Start of picture text --> Figure 5: South Africa - GDP per capita growth rate and growth acceleration and<br>deceleration<br>5<br>4<br>Growth acceleration<br>3 (1999-05)<br>2<br>1<br>0<br>-1<br>-2<br>-3 Growth deceleration<br>(1989-94)<br>-4 Growth deceleration<br>(1982-87)<br>-5<br>1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005<br><!-- End of picture text --> Pattillo, Gupta, and Carey (2005) (hereafter PGC) have applied a similar methodology to Africa only, using GDP per capita PPP growth between 1980 and 2004 from the IMF World Economic Outlook.<sup>6</sup> To address the higher volatility and lower overall rate of growth in Africa the authors use a five-year window and require that growth average be at least 2% during the acceleration.

The main differences between these two methodologies and the one proposed here are that: first, the moving average windows are bigger than ours. Second, they impose a cutoff of at least 2% in the forward minus backward moving average window, whereas we impose a cutoff of zero. Third, they impose a common minimum growth rate to define an acceleration for all countries, whereas we use the country’s growth trend as the cutoff. In general, our calculations accord with those the other two studies, but since our filter is more flexible – and identifies decelerations – it picks up more episodes; we find 32% more episodes for Africa than PGC and 114% more than HPR.

> 6 PGC calculated the growth acceleration episodes using the HPR methodology and PPP growth data. So results in Table A1 are fairly comparable to ours, despite slight differences between the IMF and WDI data. The IMF’s and WDI’s data generally follow the same pattern. However, the WDI’s GDP per capita tends to be slightly lower than the IMF’s. For a discussion on the discrepancies between the IMF and WDI GDP data see Africa Development Indicators 2006 (p. 114).

8