rafmacalaba/datause-encoder-data huggingface dataset:
Policy Research Working Paper 7378

# **Abstract**

This paper uses data from the Integrated Values Survey, the Life in Transition Survey, and the Russia Longitudinal Monitoring Survey to analyze the relation between age and subjective well-being in the Europe and Central Asia region. Although the results generally confirm the findings of previous studies of a U-shaped relation between subjective well-being and age for most of the lifecycle, the paper also finds that well-being declines again after people reach their 60s and 70s, giving rise to an S-shaped relation across the entire lifespan. This pattern generally remains robust for most of the cross-sectional and panel analyses. Hence, despite significant heterogeneity in the pattern of well-being across the lifespan in the Europe and Central Asia region, the paper does not observe high levels of cross-country or cross-cohort variation.

This paper is a product of the Poverty Global Practice Group and the Social Protection and Labor Global Practice Group. 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 authors may be contacted at Jan.Bauer@uni-hohenheim.de.

_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
42

# Table 1

(standard errors in parentheses)

||Private Credit|Quasi-Money|
|---|---|---|
|Benchmark Caset|||
|Slope|.42|.56|
||(.02)|(.03)|
|Intercept|-4.68|-6.57|
||(.11)|(.18)|
|N|2050|2028|
|e|.686|1.087|
|Robustness<br>Checks on Slopes:|||
|Aggregate Credit|.24||
||(.02)||
|M2||.19|
|||(.01)|
|Africa|.42|.47|
||(.03)|(.05)|
|Latin America|.51|.55|
||(.04)|(.06)|
|Asia|.72|.63|
||(.06)|(.08)|
|Developed<br>Countries|.29|.31|
||(.03)|(.04)|
|With<br>Time<br>Dummies|.42|.52|
||(.02)|(.02)|
|With Linear Trend|<br>.41|.63|
||(.02)|(.01)|
|5 year Averages|.40|.57|
||(.04)|(.06)|
|1950 (N=15)|.33|.12|
||(.19)|(.24)|
|1960|.55|.78|
||(.15)|(.21)|
|1970|.45|.75|
||(.09)|(.15)|
|1980|.29|.29|
||(.09)|(.11)|
|1988|.54|.36|
||(.11)|(.12)|
|Growth<br>> 3%|.41|.63|
||(.03)|(.04)|
|Growthc0|<br>.44|.52|
||(.03)|(.04'|
|Without Country Means|<br>.35|.87|
||(.03)|(.05)|
|With Inflation|.40|.54|
||(.02)|(.03)|
levels as import duties. In addition, other studies show that transportation costs often increase or escalate with product processing, a point which demonstrates that freig,. costs, like tariffs, are a constraint to further commodity processing and that transport costs have an important influence on the structure of trade. 2/ The neglect of transport costs in previous empirical analyses and policy studies may have been due to the lack of available data on their incidence or the (erroneous) assumption that these charges are exogenous variables outside the control of policy makers.

The practical importance of recent analyses of the effects of freight rates has been increased by the conclusions of related studies that indicate the level and structure of transport costs are often subject to a considerable degree of policy control. Investments in port improvements, loading facilities, or containerizad transport equipment may produce positive net benefits if resulting national gains from lower freight rates (such as an associated export expansion, or reductions in the landed price of imports), exceed the cost of the initial improvements. Shippers have also been found to to be able to lower freight costs through collective action4(see UNCTAD

- 2/ By comparing levels of nominal and effective transport protection for United States imports, Finger and Yeats (1976) concluded that transport costs generally escalate or increase with fabrication. Yeats (1977b) employed a commodity processing chain framework used for tariff analysis and demonstrated that nominal freight costs for U.S. imports generally rise as one moves from primary to semi-fabricated to processed commodities. Finally, a study by Jannsson and Shneerson (1978) estimated the long-run marginal costs (LRMC) of shipping various types of commodities and compared these figures with actual liner conference freight rates. These results showed a consisten **t** endency for LRMCs to to lie above actual freight rates for primary and semi-processed products, while the opposite effect was observed for consumption and investment goods. This lead the authors to conclude that "the principle of charging according to the value of service that is applied by conferences implies that high value commoditie **s** ubsidize low value commodities. Our results support this hypothesis. Excess freight factors escalate in a manner similar to tariffs."
law, reorganization was so inefficient that it failed to separate viable from unviable firms. Here we test whether the new Law 550 improved the efficiency of the bankruptcy system by allowing viable firms to choose reorganization as a now attractive alternative.

> **Hypothesis B1** . Before the new law, liquidating firms are indistinguishable from reorganizing firms, while after the law, liquidating firms have weaker financial health, relative to reorganizing firms.

Also as discussed in the previous section, the resulting efficiency of the reorganization procedure should result in a lower proportion of reorganization cases that end up in mandatory liquidation.

**Hypothesis B2** . The number of reorganizations that result in mandatory liquidation is lower after the new law.

# _C. Recovery after Reorganization_

As a direct result of both lower costs and better selection, the recovery of distressed firms after reorganization should improve significantly.

**Hypothesis C** . Reorganized firms recover faster after the new law.

# **IV. Data**

The data used come from the Superintendence of Companies of Colombia. We use two different datasets, bankruptcy filings and financial statements. We now explain each one in more detail.

# _A. Bankruptcy Data_

These data include the universe of liquidations (L) and reorganizations (R) filed with the Superintendence from 1995 until 2004. R firms are divided into Concordato and Acuerdo, depending on the time of the filing. Before 2000 (under Law 222), the firm filed a Concordato, while after 2000 (under the Law 550), it filed an Acuerdo.

All cases report the starting date but only about half report the ending date. Many of the ending dates are missing because the process is still ongoing, especially among 12
of data that can illuminate the nature, evolution, and consequences of inequality in SSA. However, while it will be important to improve our understanding of inequality in Africa, we also believe that we already have enough evidence to be confident that inequality is playing a key role in the persistence and reproduction of poverty in SSA. With this in mind, researchers will need to dedicate attention to the distributional patterns of the growth process itself, and to ways to increase the inclusivity of this process.

In addition to issues of distribution and growth, the research agenda that emerges will also need to dedicate attention to understanding the scope for post-outcome redistribution. This research agenda will be of interest to those in the policy sphere. The issue of taxation as a means of resource redistribution, in particular, will need to be informed by a clearer understanding of the scope for expanding the fiscal space through progressive taxation. This, in turn, will require more evidence than that which we currently have on the wealth held and income captured by top earners, much of which currently goes untaxed (Alstadsætera et al. 2014). Ultimately, a focus on the nexus between distribution and poverty may illuminate what potential Africa has for endogenous poverty alleviation, rather than a reliance on aid that, to the extent that it has led to poverty alleviation, has largely done so without a concomitant structural transformation necessary for sustained poverty reduction and inclusive growth.

22
Table 8: Self-financing decision in 2007 and 2009

|||**In 20**|**07 **||||**In 2009 1/**|||
|---|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(|3)|(4)|(|5)||(6)|
||Pro|bit|Multino|mial logit|Probit|Pr|obit|Multin|omial logit|
||||V1|V2||||V1|V2|
|VARIABLES|Buyi|n 07|(Crew in<br>07)|(Buy in<br>07)|Buyin 09|Buy|in 09|(Crew in<br>09)|<br>(Buy in<br>09)|
|IDIOSHOCK|||||0.178**|0.301**|0.134|-0.204|0.691**|
||||||(0.0694)|(0.127)|(0.0880)|(0.349)|(0.328)|
|AGGSHOCK|-0.0133|-0.0732|-1.466**|-1.306**|-0.0150|0.336***|-0.0591|-0.0368|-0.164|
||(0.0503)|(0.0569)|(0.594)|(0.616)|(0.0622)|(0.111)|(0.0752)|(0.428)|(0.430)|
|D_bad house in 07|-0.0476|-0.0693*|-0.672***|-0.942**||||||
||(0.0354)|(0.0363)|(0.226)|(0.368)||||||
|D_bad house in 09|||||0.0576|0.0706|0.0640|-0.00851|<br>0.310|
||||||(0.0501)|(0.0704)|(0.0694)|(0.279)|(0.320)|
|Boat owner and captain pre-tsunami|0.00884|0.00151|0.452|0.258|0.0696|0.0903|0.0517|0.626**|0.826**|
||(0.0398)|(0.0441)|(0.381)|(0.464)|(0.0570)|(0.0880)|(0.0791)|(0.312)|(0.323)|
|D_large boat pre-tsunami|0.0620|0.0497|-0.303|0.196|-0.00225|0.0279|0.0294|0.0679|0.0563|
||(0.0544)|(0.0544)|(0.314)|(0.355)|(0.0712)|(0.125)|(0.0990)|(0.325)|(0.450)|
|D_high income in 07|||||0.106|0.314*|0.0202|0.801**|1.038**|
||||||(0.0706)|(0.178)|(0.0802)|(0.370)|(0.436)|
|Ln(number of NGOs in 07)|-0.0819**|-0.186***|-1.368**|-2.087***||||||
||(0.0331)|(0.0562)|(0.626)|(0.572)||||||
|Ln (distance to BA)|-0.0536|-0.0844**|-0.283|-0.827**|-0.163***|0.710***|-0.173**|-0.638**|<br>-1.381***|
||(0.0416)|(0.0351)|(0.342)|(0.405)|(0.0542)|(0.191)|(0.0689)|(0.273)|(0.367)|
|Aid boats/survived fish captains|-0.0274***|-0.00753|0.176**|0.0426||||||
||(0.00938)|(0.0120)|(0.0875)|(0.100)||||||
|Constant|||4.178*|6.865***||||2.263**|2.462***|
||||(2.333)|(2.467)||||(0.914)|(0.915)|
|Observations|311|285|3|11|376|117|236||377|
|Sample||Origi|nal||||Supplementary|||
|||||||Credit<br>Union in<br>07=1|Credit<br>Union in<br>07=0|||
|Mean of dependent variable|0.148|0.161|0.486|0.148|0.312|0.299|0.342|0.470|0.313|
|Seasonality is controlled|Y|Y||Y|Y||Y||Y|
|Sampling heterogeneity is controlled 1/|||||Y||Y||Y|
|Regional fixed effects|Kab|Kec|K|ec|Kec|K|ec||Kec|

*** p<0.01, ** p<0.05, * p<0.1; Estimates in column (1), (2), (4) and (5) are marginal effects of probit model.  Column (3) and (6) provide multinomial logit estimates.  Robust standard errors clustered at the village level are in parentheses.

1/ In column (4)-(6), the inverse probability of remaining in the sample ("stayers") is used as a weight to account for attrition bias and sampling heterogeneity is controlled by including 1[ _s_orig=1_ ]. AGGSHOCK=Fraction of bad aid boats IDIOSHOCK=D_have a bad aid boat in 09
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28
# **Figure A12 – Whether people stated that COVID-19 is a big threat to their household finances disaggregated by their willingness to get vaccinated**

<!-- Start of picture text --> How much of a threat is COVID-19 to your household finances?<br>Planning on being vaccinated Not planning on being vaccinated Unsure<br>A big threat 42.6 A big threat 49.4 A big threat 58.2<br>A mild threat 35.7 A mild threat 26.5 A mild threat 19.3<br>Not much threat 21.6 Not much threat 22.6 Not much threat 21.5<br>No threat at all 0.2 No threat at all 1.5 No threat at all 1.1<br>0 20 40 60 0 20 40 60 0 20 40 60<br>Share of respondents that selected this answer<br><!-- End of picture text --> Note: This chart is based on answers to question 3 and 14 in Appendix B.

**Figure A13 – Preventive actions people took to avoid getting COVID-19 disaggregated by their willingness to get vaccinated**

<!-- Start of picture text --> 2.3<br>2.2<br>2.1<br>2<br>1.9<br>1.8<br>Planning on being vaccinated<br>Not planning on being vaccinated<br>Unsure about being vaccinated<br>Number of actions taken to avoid COVID-19<br><!-- End of picture text --> Note: This chart is based on answers to question 3, 15, 16, 17, 18, 19 and 20 in Appendix B.

36
> the same model as in _Jara-Díaz et al. (1997)_ is re-estimated, using a pool of data of 286 observations of 26 general-interest ports covering an eleven-year period (1985-1995).

> Using a similar structure as in _Jara-Díaz et al., (1997), Martínez Budría et al. (1998)_ deepen the knowledge of the Spanish port system and analyze the results of the reform of loading/unloading operations in Spanish ports.  They rely on a  database prepared from port traffic data available in the Annual Reports of Spanish ports and a survey submitted to the 34 State-owned Loading and Unloading Companies of the Spanish port system. This survey was finally completed by 24 of these companies, thus providing authors with 119 observations used to build a panel data for the 1990-1996 period. This panel is biased since not all the companies had all the information for all the sample period.

The functional specification applied to carry out the estimation is represented by the following generalized translog function: where: _C_ = Total cost, _wi_ = Price of productive factor i, _Yi_ = Amount produced of product i, _T_ = Time, α _0_ , α _i_ , α _ij_ , β _i_ , β _ij_ , θ _1_ , θ _2_ ,θ _1i_ , θ _1i_ , δ _ij_ , are parameter to be estimated. Equation (20) is estimated together with factor-derived demand equations (Shephard’s lemma) and a group of restrictions placed on the parameters commonly used in translog functions to ensure homogeneity of degree one in factor prices of the cost function<sup>18</sup> . Estimation was performed following the iterative technique modified by Zellner. This same Finally, _Tovar et al (2003)_ represents the first paper estimating a long-run total cost function for cargo handling service in multi-purpose port terminals operating in the ports of _La Luz_ and _Las Palmas_ located in Gran Canary. The paper estimates marginal costs and economies of scale and scope, not only to deepen the knowledge about a key port activity but also to contribute to the sector regulation. The database consists of a panel of incomplete monthly data about the three terminals (1991 to 1999, 1992 to 1997 and 1992 to 1998 for each of them), prepared on the basis of the information arising from the terminals, Las Palmas Port 18The following restriction ensures that cost function is homogeneous of degree one in factor prices:
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49
|**Table 7.1: Probability of Falling into Poverty- Pará u**|**rban vs. Pa**|**rá rural, 2000**<br>LR chi2(41)=|
|---|---|---|
|Probit estimates<br>Number of obs=51,|551|<br>18990.5|
|Loglikelihood= -24,255<br>PseudoR2=0.28|||
|**Dependent Variable: P0**<br>**dy/dx**|**z**|**P>|z|**|
|Age<br>-0.008|-4.86|0.000|
|Age_2<br>0.000|3.02|0.003|
|Female*<br>0.104|13.87|0.000|
|Black or Pardo*<br>0.040|6.66|0.000|
|Household size<br>-0.004|-0.8|0.425|
|Household size2<br>-0.004|-15.54|0.000|
|_<br>Household members under the age of 5<br>0.225|41.33|0.000|
|<br>Household members between age 5 and 15<br>0.195|39.35|0.000|
|Household members between age 15 and 24<br>0.080|19.11|0.000|
|Household members over age of 65<br>-0.040|-2.85|0.004|
|Primary education (1-4 grade)*<br>-0.089|-9.85|0.000|
|Lower secondary education (5-8 grade)*<br>-0.178|-19.72|0.000|
|Upper secondary education (9-12 grade)*<br>-0.308|-35.79|0.000|
|Tertiary education (>12 grade)*<br>-0.348|-31.61|0.000|
|Signed work card*<br>-0.085|-15.49|0.000|
|Employed in agriculture*<br>0.104|8.86|0.000|
|Employed in services*<br>0.098|10.82|0.000|
|Employed in industry*<br>0.095|9.66|0.000|
|Employement in the social sector*<br>0.038|3.04|0.002|
|Employed in other sector*<br>0.096|5.87|0.000|
|Rural*<br>0.035|0.48|0.631|
|Rural age<br>-0.005|-1.52|0.130|
|<br>Rural age2<br>0.000|1.92|0.054|
|_<br>Rural female*<br>-0.058|-2.6|0.009|
|Rural black and mulatto*<br>0.020|1.54|0.125|
|Rural household size<br>0.068|6.06|0.000|
|Rural household size_2<br>-0.003|-5.13|0.000|
|Rural household members under age of 5<br>-0.020|-1.79|0.073|
|Rural household members between age 5 and 15<br>-0.025|-2.42|0.015|
|Rural household members between age 15 and 24<br>-0.028|-3.04|0.002|
|Rural household members over age of 65<br>-0.118|-3.71|0.000|
|Rural primary education<br>0.035|2.24|0.025|
|Rural lower secondary education<br>0.029|1.53|0.127|
|Rural upper secondary education<br>0.016|0.63|0.528|
|Rural tertiary education<br>0.152|1.77|0.077|
|Rural signed work card<br>-0.025|-2.04|0.041|
|<br>Rural employed in agriculture*<br>-0.146|-6.44|0.000|
|Rural employed in services*<br>-0.127|-5.34|0.000|
|<br>Rural employed in industry*<br>-0.176|-8.03|0.000|
|<br>Rural employed in the social sector*<br>-0.101|-3.41|0.001|
|<br>Rural employed in other sector*<br>-0.186|-6.33|0.000|
|(*) dy/dx isfordiscrete change ofdummy variablefrom0to1|||
|Source: owncalculations based onCensus2000.|||

46
# Interrelations Among Child Mortality, Breastfeeding, and Fertility in Egypt, 1975-80

by John Marcotte and John B. Casterline

# Table of Contents

|I.|Introduction|1|
|---|---|---|
|II.|Mechanisms Linking Fertility, Child Survival, and<br>Breastfeeding|5|
||A.<br>The three events<br>B. Mechanisms|5<br>8|
|III.|<br>Data and Estimation|13|
||A. The data|13|
||B. Estimation|17|
||C. Analytic approach|19|
|IV.|Results|22|
||A. Mortality|22|
||B. Next pregnancy|26|
||C. Weaning|28|
|V.|Summary and Concluding Remarks|29|
|Table|s|33|
|Refer|ences|41|
|Appen|dices|43|