rafmacalaba/datause-encoder-data huggingface dataset:
|P081850|2004|2010|6/1/2010|16 Closed|Congo,Democratic Re|
|---|---|---|---|---|---|
|P081850|2004|2011|3/27/2011|17 Closed|Congo,Democratic Re|
|P081850|2004|2011|5/28/2011|18 Closed|Congo,Democratic Re|
|P081880|2005|2005||0 Closed|Turkey|
|P081880|2005|2006|6/21/2006|1 Closed|Turkey|
|P081880|2005|2007|1/23/2007|2 Closed|Turkey|
|P081880|2005|2007|6/29/2007|3 Closed|Turkey|
|P081880|2005|2008|5/25/2008|4 Closed|Turkey|
|P081880|2005|2009|5/1/2009|5 Closed|Turkey|
|P081880|2005|2010|2/23/2010|6 Closed|Turkey|
|P081880|2005|2011|9/12/2010|7 Closed|Turkey|
|P081880|2005|2011|5/27/2011|8 Closed|Turkey|
|P081880|2005|2012|12/31/2011|9 Closed|Turkey|
|P081880|2005|2012|6/26/2012|10 Closed|Turkey|
|P081880|2005|2013|12/26/2012|11 Closed|Turkey|
|P081880|2005|2013|5/15/2013|12 Closed|Turkey|
|P081880|2005|2014|12/14/2013|13 Closed|Turkey|
|P081880|2005|2014|6/23/2014|14 Closed|Turkey|
|P081880|2005|2015|12/31/2014|15 Closed|Turkey|
|P081880|2005|2015|6/19/2015|16 Closed|Turkey|
|P081880|2005|2016|12/24/2015|17 Closed|Turkey|
|P081880|2005|2016|5/13/2016|18 Closed|Turkey|
|P081880|2005|2017|11/28/2016|19 Closed|Turkey|
|P081882|2005|2005||0 Closed|India|
|P081882|2005|2019|5/7/2019|1 Closed|India|
|P081907|2004|2008||0 Closed|Indonesia|
|P081909|2003|2003||0 Closed|Pakistan|
|P081909|2003|2004|5/13/2004|3 Closed|Pakistan|
|P081909|2003|2005|4/19/2005|5 Closed|Pakistan|
|P081909|2003|2006|10/3/2005|6 Closed|Pakistan|
|P081924|2003|2003||0 Closed|Congo,Republic of|
|P081924|2003|2004|6/30/2004|2 Closed|Congo,Republic of|
|P081924|2003|2005|6/30/2005|3 Closed|Congo,Republic of|
|P081924|2003|2006|12/22/2005|4 Closed|Congo,Republic of|
|P081924|2003|2006|5/31/2006|5 Closed|Congo,Republic of|
|P081924|2003|2007|11/17/2006|6 Closed|Congo,Republic of|
|P081924|2003|2007|5/17/2007|7 Closed|Congo,Republic of|
|P081924|2003|2007|6/28/2007|8 Closed|Congo,Republic of|
|P081924|2003|2008|11/16/2007|9 Closed|Congo,Republic of|
|P081924|2003|2008|4/15/2008|10 Closed|Congo,Republic of|
|P081924|2003|2009|10/15/2008|11 Closed|Congo,Republic of|
|P081924|2003|2009|12/24/2008|12 Closed|Congo,Republic of|
|P081950|2004|2004|6/28/2004|1 Closed|Romania|
|P081950|2004|2005|4/11/2005|3 Closed|Romania|
|P081950|2004|2005|6/22/2005|4 Closed|Romania|
|P081950|2004|2006|5/18/2006|5 Closed|Romania|
|P081950|2004|2007|7/20/2006|6 Closed|Romania|
WPS4173 Pathways out of poverty during an economic crisis: An empirical assessment of rural Indonesia

# Neil McCulloch<sup>1</sup> Julian Weisbrod<sup>2</sup> C. Peter Timmer<sup>3</sup>

## **Summary**

Most poor people in developing countries still live in rural areas and are primarily engaged in low productivity farming activities. Thus pathways out of poverty are likely to be strongly connected to productivity increases in the rural economy, whether they are realized in farming, in rural non-farm enterprises or by rural-urban migration. We use cross-sectional data from the Central Statistical Board for 1993 and 2002, as well as a panel data set from the Indonesia Family Life Survey for 1993 and 2000, to show which pathways out of poverty were most successful over this period. Our findings suggest that increased engagement of farmers in rural non-farm enterprises is an important route out of rural poverty, but that most of the rural agricultural poor that exit poverty still do so while remaining rural and agricultural. Thus changes in agricultural prices, wages and productivity still play a critical role in moving people out of poverty.

## World Bank Policy Research Working Paper 4173, March 2007

_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._

### **Acknowledgements**

Our greatest debt is to Lina Marliani. She faithfully compiled the datasets used in this paper and produced many of the graphs and tables. In addition we would like to thank BPS for use of the data and DFID for funding the work of the INDOPOV team in the World Bank Office in Jakarta under which most of this work was done. Finally we would like to thank numerous colleagues in Jakarta, Göttingen, Washington and elsewhere for useful comments and suggestions.

> 1 Neil McCulloch, Senior Economist, World Bank Office Jakarta.  Corresponding author: <u>nmcculloch@worldbank.org</u>

> 2 Julian Weisbrod, University of Göttingen, Germany.

> 3 C. Peter Timmer, Center for Global Development, Washington D.C.

1
So far, the best way to disseminate the mechanisms and their scope has been through the businessmen who have presented cases, the advisors who have studied the cases, former officials and other related professionals, who are generating a considerable degree of maturity and knowledge in the private sector.

<u>Inter-agency Support.- There is no Inter-agency cooperation in formal or regular terms.</u> During some phases of the CDS, there has been informal but close cooperation with Mexico's SECOFI. Authorities say that their cooperation needs are channeled through Peru’s trade delegations abroad, especially in Geneva and the WTO. A frequent complaint is that formal foreign cooperation does not always reach investigating authorities, because the formal channels that should be used constitute a limitation and sometimes cooperation is wrongly channeled.

# **B. Peru’s Cases**

# **_2. Overall Results_**

# _(a) Outcomes of Investigation Applications_

A total of 81 trade defense applications were submitted to the CDS since it was created in 1999 until now . Most (70) correspond to cases of alleged dumping; 7 were claims for subsidies, and only 4 were requests for safeguard clauses. Of the total, one out of four applications (21%) was considered inappropriate or was withdrawn by the applicant, and therefore an investigation was not initiated.

**Table 4.  Applications and Measures, 1993-2004**

||Total|Subsidies|Safeguard|Dumping|
|---|---|---|---|---|
|Applications|81|7|4|70|
|Investigations|64|5|2|57|
|Provisional Duty|_30_|_3_|_1_|_26_|
|Provisional and Founded|_23_|_2_||_21_|
|Founded|28|2||26|
|Partially founded|4|1||3|
|Unfounded|28|2|1|25|
|Pending Resolution|4||1|3|

Source: INDECOPI Note: Two cases that were presented but subsequently withdrawn by the petitioner are included in the total for Unfounded Cases.

Of the 64 applications admitted for an investigation, two were withdrawn by the applicants. Provisional duties were applied in 30 cases, of which 26 were dumping cases. Of the latter, 21 eventually led to definitive duties and 5 were declared unfounded.

20
sample with valid responses, 18.8% replied affirmatively. Despite some ambiguity regarding the term “attempted,” we use this variable as a proxy for whether firms actually submitted a bid for a government contract. We are thus assuming that firms that are deterred from actually submitting a bid by high transactions costs, lack of information, distrust in the integrity of the process, etc., do not report that they attempted to obtain a contract.

For firms replying in the affirmative to this first question, a second question asks: “When establishments like this one do business with the government, what percent of the contract value would be typically paid in informal payments or gifts to secure the contract?” Bribe-paying is a sensitive issue so the question asks about “establishments like this one” instead of specifying “your establishment” to encourage candor. We follow common practice in using responses as a proxy for the firm’s own payments (World Bank, 2000).<sup>5</sup> Among the 5,371 firms in our sample that report they attempted to secure a government contract, 1,050 replied that an informal payment was needed, with an average payment of 11.6% of the contract value. Among all 5,371 firms, including those reporting that no payment (0%) is needed, the average value is 2.3%.

The World Bank’s Enterprise Surveys have been used in numerous research studies, but the procurement questions have received relatively little attention. World Bank (2002) reports that informal payments for obtaining government contracts tend to be larger for smaller and privatelyowned firms, and lower for foreign-owned firms, in an analysis of over 6,500 firms in Enterprise Surveys conducted in 2002 in 26 transition countries. World Bank (2005) has similar findings regarding firm ownership, in a later round of surveys for the same set of countries, and reports that the “kickback tax” – its term for informal payments for obtaining public contracts - is higher on average for younger firms.

Kisunko et al. (2013) analyze data from a Russian Federation Enterprise Survey with 4,223 firms, designed to be representative at the level of 37 regions. Of the 27% of firms reporting that they attempted to obtain a government contract, 23% stated that an informal payment was needed, and that the required payments averaged 15% of the contract value. Firm-level characteristics were mostly not significant in explaining differences in these informal payments. However, such payments were

> 5 Some managers responding to the survey may not be well informed about their firms’ payments, adding one more source of measurement error.

7
6 times greater (12 dollars) than the lower threshold and 5 times greater than the upper (50 dollars). Both intervals can be reasonable but they define two completely different groups.

A further complication one might encounter in low/lower middle income countries is defining an upper bound. In general, household surveys do not contain good estimates of upper percentiles of welfare (Alvaredo and Piketty, 2010).<sup>5</sup> When using consumption to rank welfare, as it is normally done in low/lower middle income countries, the situation is further aggravated. Consumption is very accurate in capturing the well-being of poorer people, yet it is rather imprecise in capturing that of people living in upper percentiles. It follows that when defining middle class in these countries, it seems reasonable to opt for a lower bound threshold (middle class and above) rather than an interval and leave the border between middle class and upper class somehow undefined.

Before turning to the data and methodology section, in the next paragraphs, we examine the available studies on the middle class in Sub-Saharan Africa (SSA) and Nigeria in particular. Whereas the economic debate on existence and definition of the middle class has become particularly lively in many developing countries, the issue has thus far received limited attention in Sub Saharan Africa with the notable exception of South Africa. There is, however, increasing awareness that a strong middle class can potentially change the economic and political landscape of African societies.

# _An emerging African middle class?_

The emergence of the African middle classes has so far been studied by sociologists and political scientists, documented through international and national press, but mostly ignored by the academic economic literature. Among various authors, there is a general consensus that the middle class produces economic benefits for society as a whole and broadens the base of economic development. Also, in the recent growth acceleration of some African economies the middle class demand for goods and services seems to have played an important role (McKinsey, 2010). On the political side, the middle class played a role in the democratization process that started in the nineties (Southall, 2004). Throughout SSA, the middle class was the determinant in obtaining fair elections, reliable institutions and freedom of press and opinion.

> 5The reason for measurement issues at the upper percentiles is due to under-reporting (Alvaredo and Piketty, 2010). Alavredo and Piketty skirt this issue by relying on tax data, however in low/lower middle income countries tax systems are not as thoroughly developed.

6
**Table 4.** Distribution of employment elasticities in South Asia.

|**South Asia**|**Elasticity**|
|---|---|
|25<sup>th</sup> percentile|0.10|
|Median|0.20|
|75<sup>th</sup> percentile|0.60|
|Mean|0.34|
|Long-run|0.19|

**Source:** All comparable surveys highlighted in Table 1.

We report employment elasticities by country, sector of activity and type of job in Table 5, while also providing a breakdown by gender. Except for Bhutan, faster growth in South Asian countries has translated into more employment. The employment elasticity has been very low in India, driven by a negative elasticity in the case of female employment. Conversely, the elasticity is high in Pakistan, driven by a positive elasticity for female employment. However, the sectoral breakdown shows that in the case of Pakistan, the growth elasticity of female employment in agriculture is huge, whereas it is negative in India.

For most South Asian countries, the employment elasticity was strongest for the manufacturing sector. While jobs created in the manufacturing sector benefitted mainly male workers, the opposite was true in the services sector. In Sri Lanka, for example, the employment elasticity of the services sector was zero for men, but 0.5 for women. The elasticity of regular wage employment was especially high in Bangladesh, which can partly be explained by the large growth of manufacturing employment in urban areas (Farole and Cho 2017). In all countries the elasticity of regular wage employment is higher for women than for men.

**Table 5.** Employment elasticities by sector of activity and type of job.

|**C**|**Y**|**S**||**El**||**Indu**|**stry**|||**Emplo**|**yment ty**|**pe**|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|**ounr**|**ears**|**urve**||**momen**|||||||||
||||||||||||**elf-**||
||||||**Agriculture**|**Manufacturin**|**g**<br>**Service**|**Construction**|**Regular**|<br>**Casual**|**employed**|**Unpaid**|
||||Total|0.23|-0.05|0.84|0.37|1.00|0.96|0.07|0.23|-0.26|
|Bangladesh|<br>2002 -<br>2015|LFS|Male|0.17|-0.18|1.09|0.34|1.01|0.84|0.05|0.11|-0.44|
||||Female|0.43|0.35|0.46|0.52|0.80|1.40|0.19|1.09|-0.13|
||||Total|-0.04|-0.26|2.37|1.07|1.26|n/a|n/a|-0.19|-0.34|
|Bhutan|2003 -<br>2012|LSS|Male|0.08|-0.21|3.04|0.98|1.10|n/a|n/a|-0.24|-0.30|
||||Female|-0.17|-0.30|1.41|1.32|2.91|n/a|n/a|-0.12|-0.38|
||||Total|0.07|-0.16|0.16|0.28|1.16|0.41|0.08|0.12|-0.28|
|India|2004 -<br>2011|NSS-<br>Thick|Male|0.18|-0.03|0.21|0.29|1.15|0.40|0.24|0.14|-0.15|
||||Female|-0.20|-0.38|0.01|0.26|1.25|0.45|-0.27|0.01|-0.40|
||||Total|0.86|0.81|1.24|0.68|1.47|0.67|0.89|1.23|0.59|
|Pakistan|2005 -<br>2014|LFS|Male|0.70|0.36|1.18|0.67|1.49|0.65|0.82|0.94|0.02|
||||Female|1.57|1.83|1.50|0.68|-0.41|0.78|1.36|4.07|1.28|
||||Total|0.21|0.09|0.17|0.15|n/a|-0.10|0.75|0.33|0.02|
|Sri Lanka|2001 -<br>2015|LFS|Male|0.16|0.06|0.12|0.04|n/a|-0.16|0.67|0.24|-0.29|
||||Female|0.31|0.13|0.23|0.52|n/a|-0.01|0.99|0.71|0.19|

**Note:** n/a: information not available. **Source:** South Asia Employment Dataset.

17
The final column is shaded, to indicate that for this outcome, lower values reflect better outcomes. Thus negative signs should be interpreted as reforms helping improve the outcome. The indicator is drawn from DHS surveys regarding domestic violence and the share of women who could face a beating for arguing, refusing sex or burning the food. The country coverage is low, but both equal inheritance and non-exemption of customary law are associated with lower rates of women fearing being beaten.

# _Time series analysis_

For the series with the longest time series dimension, Table 3 looks at the effect of reforms of each legal indicator.<sup>6</sup> The same set of controls is again included. We also allowed for non-linear effects by income. It should be noted that some of the coefficients are quite large, with offsetting interaction effects. This reflects that there is a sizeable variation in the outcome variables across countries – including those with and without reforms. The claim is not that strengthening women’s rights on its own will automatically lead to large improvements in outcomes; but there are significant differences on average between countries with and without gender gaps in rights, controlling for a number of time-varying and non-varying country characteristics.

In terms of women’s labor force participation, there are differential effects by level of income; the effect of the reforms in raising labor force participation is almost always stronger in middle- and upper-level-income countries. The inflection point comes in close to the median of the sample; so the beneficial impacts are relevant for a large number of countries. At the median

> 6 There is no time series dimension available on the variables measuring women’s access to bank accounts or loans; the coverage of the share of women as senior officials and managers is likewise thin and there is no repeating information on the measure of domestic violence.  The coverage of female infant mortality is less extensive than of infant mortality overall, so we look at the latter measure in the panel analysis. The same is true of ‘the age of first marriage’ compared to ‘the share of 18 year olds who are married.’

20
Table 8: Job tenure

|||Log (tenur|e in years)||
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|Social networks|-0.152<sup>_∗_</sup>|-0.166<sup>_∗_</sup>|-0.122|-0.197<sup>_∗_</sup>|
||(0.090)|(0.099)|(0.100)|(0.109)|
|Schooing in years||-0.008|-0.004|-0.009|
|||(0.008)|(0.009)|(0.010)|
|Age at hire||-0.010|-0.012<sup>_∗_</sup>|-0.005|
|||(0.006)|(0.007)|(0.006)|
|Father’s pri.school||-0.019|-0.042|-0.072|
|||(0.060)|(0.063)|(0.062)|
|Mother’s pri.school||0.040|0.018|0.049|
|||(0.052)|(0.059)|(0.072)|
|Math z-score||-0.020|0.034|0.035|
|||(0.043)|(0.056)|(0.058)|
|Language z-score||0.071|0.060|0.040|
|||(0.053)|(0.052)|(0.057)|
|Big 5 index z-score||0.066|0.085|0.158<sup>_∗_</sup>|
|||(0.055)|(0.082)|(0.085)|
|Firm fxed efect|||X||
|Firm-occ fxed efect||||X|
|R-squared|0.013|0.024|0.018|0.026|
|N|3396|3390|3390|3390|

_Note_ . The dependent variable log( _tenure_ ) is constructed by treating 0 year of tenure as 0.5 year, 1 year as 1.5 year, and so forth. The other controls included are establishment-entry occupation fixed effects and geographical division fixed effects. Standard errors clustered within an establishment are in parentheses. Significance levels:<sup>_∗∗∗_</sup> = 1%,<sup>_∗∗_</sup> = 5%,<sup>_∗_</sup> = 10%.

30
# Introduction

There have been many calls to make infrastructure systems more resilient, in part triggered by recent large‐scale disasters. However, it is not straightforward to evaluate the costs and the benefits of more resilient infrastructure and make a quantified economic case for investing more in this domain.

Two challenges make such an assessment particularly difficult. Firstly, the cost of making new infrastructure more resilient depends on the type and quantity of infrastructure that is being built, which is very uncertain and depends on many external factors. Secondly, there are large uncertainties on the cost of making infrastructure more resilient, as well as the effect of such efforts on future repair and maintenance costs, and on the future frequency and duration of infrastructure disruptions. As a result, providing a single estimate of the benefit‐cost ratio or the economic benefit from more resilient infrastructure has been difficult.

To provide new evidence on this issue, this paper proposes a cost‐benefit analysis with a systematic exploration of the large uncertainty that surrounds many parameters of the analysis, and explores the desirability and robustness of more resilient investment, using principles inspired from the robust decision‐making methodology (Lempert et al. 2006).

It starts from a set of scenarios on future infrastructure investments, from Rozenberg and Fay (2019). Then, it reviews the technical options (and their associated costs) to make infrastructure more resilient, based on a study by Miyamoto International (2019). It applies this incremental cost to the baseline investment needs scenarios developed by Rozenberg and Fay. An exploratory modelling approach considering thousands of scenarios is then used to explore the benefit‐cost ratio of these options.

# Future infrastructure investment needs

Rozenberg and Fay (2019) uses a systematic approach to estimate the funding needs (capital and operations and maintenance) for closing the service gap in water and sanitation, transportation, electricity, irrigation, and flood protection by 2030. (Telecommunications is not included in their analysis because it is mostly privately funded.) They estimate that new infrastructure could cost low‐ and middle‐income countries between 2 percent and 8 percent of their GDP a year to 2030, depending on the quality and quantity of infrastructure services sought and the spending efficiency achieved to reach this goal (table 1). Moreover, with the right policies, investments of 4.5 percent of GDP could enable low‐ and middle‐income countries to achieve the infrastructure‐related Sustainable Development Goals and stay on track to full decarbonization by the second half of the century.

2
focuses on the main countries affected by antidumping or countervailing duties. Until 2003, duties were still imposed on products from 10 countries. The country upon which the highest number of duties has been imposed is China (34.2 % of total duties), followed by the United States (28%), South Korea (8.1%) and Russia (6.3%).

**Table 5 - Initiated Investigations, Antidumping and Countervailing Duties by Country, 1987-2002**

|#|**Country**|**Number of**<br>**investigations**|**Percentage of**<br>**total**<br>**investigations**|**Number of**<br>**duties in**<br>**effect in 2002**|**Percentage of duties**<br>**vis-à-vis the number**<br>**of investigations**|
|---|---|---|---|---|---|
|1|UnitedStates|68|27.09%|13|19.12%|
|2|China|46|18.33%|36|78.26%|
|3|Brazil|25|9.96%|4|16.00%|
|4|Venezuela|10|3.98%|1|10.00%|
|5|South Korea|9|3.59%|2|22.22%|
|6|Germany|7|2.79%|||
|7|Russia|6|2.39%|5|83.33%|
|8|Spain|7|2.79%|||
|9|Taiwan|6|2.39%|2|33.33%|
|10|Ukraine|6|2.39%|3|50.00%|
|11|Canada|5|1.99%|||
|12|European Union|4|1.59%|2|50.00%|
|13|Colombia|4|1.59%|1|25.00%|
|14|Japan|3|1.20%|1|33.33%|
|15|Indonesia|2|0.80%|1|50.00%|
||Other countries|43|18.40%|8|18.60%|
||Total|251|100|79|31.47%|

Source: Based on data from UPCI’s _Informe de Labores_ , 2002.

It is interesting to compare the number of duties in effect to the investigations concluded for each country. Despite the fact that the greatest number of investigations was initiated against products of US origin, only 19% of concluded cases involving the United States have duties in force. By contrast, the percentage of duties in force vis-à-vis the investigations concluded in relation to China and Russia is 78% and 83%, respectively (see Table 5 above). This asymmetry also stems from the different standards applied by the UPCI to market-oriented and nonmarket economies.

> 51 See Table 12, in the final considerations of this chapter.

21