rafmacalaba/datause-encoder-data huggingface dataset:
impact with operating expenditures as input but technically efficiency dropped when considering total expenditures (Motta, 2004). This makes case for including capital costs in any benchmarking exercise. Overall, the reform processes as well as the incentives generated in the reform process in Brazil do not seem to have led the firms to behave in a more efficient manner between 1998 and 2005 (Ramos-Real et al., 2009).

Bonifaz and Santin (2000) found out that privatised firms did not outperform state enterprises arguing that privatisation did not lead to an improvement in terms of efficiency among Peruvian electricity distribution companies. The post reform experience suggested insufficient evidence for technical change or significant savings associated with technological improvements in the sector (Bonifaz and Rodriguez, 2001). Improvements in efficiency and productivity of electricity distribution in Peru have occurred with the adoption of regulatory reforms in the Peruvian electricity sector although privatisation proved to be advantageous only in the initial years after the reform (Perez-Reyes and Tovar, 2010). There seem to be a positive relationship between the restructuring and reforms of the electricity distribution sector and enhancement of productivity in Peru (Perez-Reyes and Tovar, 2009). Management practices seem to be important in the Peruvian electricity distribution due to which private utilities are less inefficient than public utilities (Bonifaz and Jaramillo, 2010).

In Colombia, reforms of the 1990s seem to have improved the average efficiency levels of electricity distribution with regulatory policy engendering a positive effect while ownership has produced no conclusive effect (Pombo and Ramirez, 2002a). Technological improvements and regulatory policy have had a positive effect on average efficiency but the divide between good performers and bad performers increased after reforms (Pombo and Ramirez, 2002b). Mello and Espinoza (2004) found no significant changes in the productivity levels among the 20 distribution companies between 1993 and 2003, although environmental variables mattered significantly. In contrast, Pombo and Taborda (2006) showed that plant efficiency and productivity increased after the regulatory reform of 1994 although the efficiency of distribution companies did not improve after the reforms. Nonetheless, the Colombian electricity distribution exhibits high inefficiency persistence and heterogeneity among firms (Galan and Pollitt, 2014). Rural companies and firms with small customers seem to have experienced the largest efficiency gains over the 15 years after the reforms.

In Sub-Saharan Africa, the results obtained from the efficiency analysis of the Côte d’voire electricity companies could not reject the hypothesis of a significant performance improvement 25
13 The parameter α is intended to capture the (short-run) pass-through from agricultural prices to agricultural wages, and is clearly key to the analysis. One benchmark value would correspond to a perfectly competitive agricultural labor market, where wages are equal to the marginal revenue product of labor. If labor supply is perfectly inelastic in the short-run – because workers are immobile in that time-frame, say – then α=1.0. To the extent that the elasticity of labor supply rises (say, in the medium run), or that employers have some market power and can capture as profits part of the price gains, then α < 1.0. We use two benchmark cases, as an illustration of these two main possibilities: α =1.0 and α =0.5.

The third term in (6), corresponding to the transfer income effect, is meant to capture changes in the values of transfers received by Brazilian households, with the objective of mitigating the food price increases. Strictly speaking, it is not obvious that such policy responses should be treated as part of the economy‟s general equilibrium adjustment to the price changes. They might, however, be seen as part of the overall “political economy” equilibrium, and an assessment of their protective effect across the income distribution (or lack thereof) may well be of policy interest.

Specifically, the benefit amounts in two large social assistance programs – Bolsa Família and the Benefício de Prestação Continuada (BPC) – were raised during 2008 and, in at least one case, with the explicit aim of mitigating the food price increases.<sup>6</sup> Bolsa Família is a conditional cash transfer program that reaches over 12.5 million households. The benefits vary according to household composition and monthly per capita income. The basic benefit was raised from R$50 to R$54 per household in July 2008. The BPC is a means-tested old-age non-contributory pension and disability grant program. It transfers a benefit equivalent to the minimum wage to elderly and disabled individuals whose household income is less than one quarter of the minimum wage. Its value was raised by 10% in March 2008, in line with the increase in the national minimum wage. We used these increase values to compute for each household that declared receiving either one of these benefits in the 2006 PNAD.<sup>7</sup> The transfer income effect was set to zero otherwise.

> 6 “Minister Patrus Ananias (Social Development) said on Wednesday that the average Bolsa Família benefit will rise from R$78.70 to R$80.00. He added that the 8% value of the increase [in the basic benefit] was determined on the basis of the INPC (Índice Nacional de Preços ao Consumidor), _with the objective of improving the purchasing power of low-income families in the midst of the world food crisis_ ” (Folha de São Paulo newspaper, online, 25 June 2008, our translation and emphasis).

> 7 Subsequent to these increases in the transfer amounts, the programs were also expanded on the extensive margin, to cover additional households. These effects are not captured by the analysis.
WPS3713

**Empowerment and Local Level Conflict Mediation in Indonesia: A Comparative Analysis of Concepts, Measures, and Project Efficacy**<sup>1</sup>

Christopher Gibson _Brown University_ Michael Woolcock _World Bank and Harvard University_

# _Abstract_

The notion of ‘empowerment’ has been more often deductively claimed than carefully defined or inductively assessed, by development scholars and practitioners alike. We define and assess empowerment through an in-depth examination of the extent to which a large community development project in rural Indonesia empowers participants (especially members of marginalized groups) through building their capacity to manage local conflict. Although the project induces conflict through its deployment of a competitive bidding process, we argue that, when well implemented, it can also enable otherwise unequal groups to more peacefully, equitably, and effectively engage one another. Using a mixed methods approach, we compare cases from otherwise similar ‘treatment’ and ‘control’ villages to shed light on the chief components of villagers’ capacity to manage local conflict. We discuss the interdependencies of two major analytical realms—routines of inter-group collaboration, and sources of ‘countervailing power’—and their relation to local conflict processes and outcomes.

# World Bank Policy Research Working Paper 3713, September 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._

> 1 This paper is part of a larger study on local level conflict and participatory development projects in Indonesia. For generous financial assistance we are grateful to DfID, AusAID, the Norwegian Trust Fund (Measuring Empowerment Study), and the World Bank’s Conflict Prevention and Reconstruction Unit, and Development Economics Vice Presidency (Research Support Budget).  Patrick Barron, Claire Smith, Rachael Diprose and Adam Satu were key members of the research team, and played an integral role in developing the ideas explored here. Other field-level researchers provided ideas throughout the study.  We are also indebted to Scott Guggenheim and Ruth Alsop for their active support and feedback, and to Dan Biller and Patrick Barron for helpful comments. Address for correspondence: Michael Woolcock, Mailstop MC3-306, 1818 H Street NW, Washington, DC 20433, USA.  Email addresses: christopherlgibson@gmail.com, <u>mwoolcock@worldbank.org.</u>
more stable funding model, reflected in high loan-to-deposit ratios (LDR) and much greater reliance on foreign funding (FOREIGN FUNDING).

In this section we provide further evidence on the factors that drive the differences in ECA and the rest of the world. While all three factors – LDR, FOREIGN FUNDING and FOREIGN OWNERSHIP – are higher in ECA, not all factors are high in all countries at the same time, as we discussed above. This allows us to investigate which of the three factors is driving the difference between ECA and non-ECA in terms of the response of private credit to foreign funding shocks. In doing so, we adopt the following procedure. First, we create “truncated ECA samples” by removing countries that are high on one of the characteristics that we are interested in—FOREIGN OWNERSHIP, FOREIGN FUNDING, and LDR. Such a “truncated ECA sample” is more similar to the rest of the world in terms of the selected characteristic (i.e. FOREIGN FUNDING), but can be different in terms of the other two characteristics (i.e. LDR and FOREIGN OWNERSHIP). Then we run PVARs on both samples and compare the results of the “truncated ECA sample” with the rest of the world. We do this subsequently for each of our three variables of interest. If we still find a difference between ECA and the rest of the world, we conclude that the specific characteristic appears not to be driving such difference (and vice versa). Table 4, Panel C provides the summary statistics of the various truncated ECA samples.

First, we remove from the ECA sample countries that are high on FOREIGN FUNDING. We use the pre-crisis median of FOREIGN FUNDING to construct this truncated sample. The resulting sample contains ECA countries with relatively low FOREIGN FUNDING. However, even the relatively low FOREIGN FUNDING countries in ECA still have significantly higher FOREIGN FUNDING (20% in the truncated ECA sample, vs. 11% in the non-ECA sample). This stacks the cards towards confirming the differential impact in the truncated ECA sample and the non-ECA sample. We then compare the truncated ECA sample with the non-ECA sample. Figure 7 presents the differences between the samples in the impulse-responses of the response of PRIVATE CREDIT to a FOREIGN LIABILITIES shock. Graph in row 1, column 1 shows that the difference between the truncated ECA sample and non-ECA sample is not significantly 26
unit of transfer more than the average UCT intervention. In addition, the TUP interventions in our sample preceded the UCT interventions by 4 years on average, and as a result estimates are on average 1.1 years since last transfer later. In Section 6, we conduct analysis benchmarking the impacts of TUP against UCT interventions, and test robustness to adjusting for key differences between the TUP and UCT interventions in our sample.

# **3 Metaänalysis**

## **3.1 Estimation strategy**

Our objective is to aggregate estimates of the impacts of UCT from a set of randomized control trials (RCTs), each of which may have multiple UCT arms and multiple survey waves. Before testing for evidence of nonlinearities, we begin with a traditional metaänalysis, estimating both the average impact of UCT across estimates and heterogeneity in impacts across contexts. We let _r_ index RCTs, _a_ index experimental arms within RCT, and _t_ be years since the last transfer for each estimate. We observe a set of estimates _τ_ ˆ _rat_ of the impact of UCT on household consumption per unit of transfer for arm _a_ of RCT _r_ , _t_ years since the last transfer, in addition to the standard error on each estimate seˆ _rat_ .

We model these estimates as reflecting a combination of both sampling error and true variation in impacts across contexts. Following recent metaänalyses in economics (Baird et al., 2014; Burke et al., 2015; Meager, 2019; Vivalt, 2020), we specify where _τrat_ is the true impact of arm _a_ of RCT _r_ , _t_ years since the last transfer. The first line of Equation 1 states that the estimated effect is normally distributed, is unbiased for the true effect, and has variance equal to the reported standard error squared.<sup>8</sup> The normality

> 8We note that this implicitly imposes no within RCT correlation between estimated effects, while within

15
The remainder of this paper is structured as follows. Section 2 presents background information on trade and investment integration in Pakistan. Sections 3 and 4 describe the data used and the empirical strategy. Section 5 presents the results and discusses the underlying channel, and Section 6 concludes.

# **2. Productivity, Trade, and Investment Integration Trends in Pakistan**

Long-term trends of macro indicators on productivity for Pakistan – both total factor productivity (TFP) and labor productivity – show relatively low rates of growth when compared with other countries in the region.<sup>5</sup> While labor productivity has been increasing since the turn of the century, its rate of growth has fallen with respect to that of the previous decades, and lower than that observed in India or Bangladesh.

Figure 1– TFP and Labor Productivity (19812017, Pakistan and Comparators) <!-- Start of picture text --> 7<br>6<br>5<br>4<br>3<br>2<br>1<br>0<br>TFP LP LP India LP<br>Pakistan Pakistan Bangladesh<br>Average growth rate<br>81-90 91-00 01-17 81-90 91-00 01-17 81-90 91-00 01-17 81-90 91-00 01-17<br><!-- End of picture text --> Note: Authors’ calculation based on the APO Productivity Database 2019.

Figure 2– Capital Deepening (1981-2017, Pakistan and Comparators) <!-- Start of picture text --> 5<br>1980s<br>1990s<br>4 2000s<br>2010s<br>3<br>2<br>1<br>0<br>Pakistan India Bangladesh<br>Capital deepening<br><!-- End of picture text --> Note: Authors’ calculation based on the APO Productivity Database 2019. Capital deepening indicates the rate of change in capital stock per labor hour.

A similar pattern is observed for TFP (Figure 1). In the international comparison, Pakistan also does not fare well. Since 2000, labor productivity grew at an average rate of 1.5 percent annually, substantially below what is observed in India (6 percent) and Bangladesh (4.4 percent). This can be partly explained by the slowdown in capital deepening – the increase in the stock of capital per worker. Indeed, while India and Bangladesh have experienced positive growth in capital per worker over the past decades (Figure 2), in Pakistan, capital per worker has been growing at a declining rate, and has practically stagnated since 2010.

Policy measures of integration also show some stagnation. According to the Overall Trade Restrictiveness Index (OTRI), Pakistan is currently the world’s seventh most-protected economy

> 5 These macro indicators on productivity are obtained from the APO Productivity Database, based on a Solow decomposition, assuming constant returns to scale, and perfect competition.

5
prospects of women relative to men may also be affected by annual global shocks such as those stemming from changes in technology, world trading system, and international capital flows.

Regarding firm-level factors, firm-size and age could impact female employment directly by influencing firms’ preference and costs for discrimination (see Vo and Ha 2021, Zhang et al. 2021, and Bratti et al. 2005). Firm-size and age may also influence skill requirement, labor productivty, export orientation, and foreign ownership, which may in turn affect female employment. Firm size may also affect application of law. Several countries have stricter employment protection laws for large firms than small firms suggesting that larger firms may find it more difficult to discriminate against female workers. On the other hand, smaller and younger firms tend to face greater competition in the product market. More competition is often linked with lower discrimination and therfore higher women’s employment (see Cooke et al. 2019). There is also evidence to suggest that lack of proper skills or labor market discrimination may force women to work in firms that pay lower wages (Card et al. 2016). Thus, we may expect more female workers in firms that are less productive and dynamic in terms of growth rate and R&D activity. Exporting status has been linked with greater demand for female workers in several studies (see World Bank 2020, Juhn et al. 2014). There is also a small but growing body of work showing that foreign direct investment may improve the share of female workers through different channels including transplantation of more female-friendly foreign cultural norms (see Kodama et al. 2018, Ouedraogo and Marlet 2018). We also consider the gender of the firm’s owners and top manager. Female owners can be expected to discriminate less against female workers than their male counterparts, although the evidence on the issue is mixed (see Bossler et al. 2020, Bertrand et al. 2019, Nelson and Bridges 1999). Women may be more affected than men by crime as women are more likely to be the targets of criminal activities (Mishra et al. 2021, Islam 2013). In many 8
# **INCENTIVE COMPATIBLE REFORMS: THE POLITICAL ECONOMY OF PUBLIC INVESTMENTS IN MONGOLIA**

## **Zahid Hasnain**<sup>*****</sup>

## **JEL Codes: H41, H54, D72**

> _Acknowledgements_ :  This paper has benefitted greatly from comments by Richard Allen, Jim Brumby, Coralie Gevers, Phil Keefer, Yasuhiko Matsuda, and Rob Taliercio.

> * The World Bank

1
# **3.2.2 Pair-wise matching**

As a third method, we simulate pair-wise matching. As opposed to stratification, matching provides a method to improve covariate balance for many variables at the same time. Greevy et al. (2004) describe the use of optimal multivariate matching. However, we chose to use the less computationally intensive “optimal greedy algorithm” laid out in King et al. (2007)<sup>13</sup> . In both cases pairs are formed so as to minimize the Mahalanobis distance between the values of all the selected covariates within pairs, and then one unit in each pair is randomly assigned to treatment and the other to control.

As with stratification, matching on covariates can increase balance on these covariates, and increase the efficiency and power of hypothesis tests. King et al. (2007) emphasize one additional advantage in the context of social science experiments when the matched pairs occur at the level of a community or village or school, which is that it provides partial protection against political interference or drop-out. If a unit drops out of the study or suffers interference, its pair unit can also be dropped from the study, while the set of remaining pairs will still be as balanced as the original data set. However, the converse of this is that if units drop out at random, the matched pair design will throw out the corresponding pairs as well, leading to a reduction in power and smaller sample size than if an unmatched randomization was used.<sup>14</sup>

# **3.2.3 Re-randomization methods**

Since our survey revealed that several researchers are using re-randomization methods, we simulate two of these methods. The first, which we dub the “big stick” method by analogy with Soares and Wu (1983), requires a re-draw if a draw shows any statistical difference in means between treatment and control group at the 5 percent level or lower. The second method picks the draw with the minimum maximum t-stat out of 1000 draws.

> 13 The Stata code performing pair-wise Mahalanobis matching with an optimal greedy algorithm takes several days to run in the 300 observations sample. If there is little time in the field to perform the randomization this may thus not be an option. It is thus important to have ample time between receiving baseline data and having to perform the randomization to have the flexibility of using matching techniques if desired. Software packages other than Stata may be more suited for this algorithm and may speed up the process.

> 14 See Greevy et al. (2004) for discussion of methods to retain broken pairs.

- 14 -
# **2.1 Sample**

Although the WBG has more than 100 country offices, we restrict our sample to staff in the Washington headquarters hired on a U.S. dollar salary plan, commonly known as “internationally recruited staff.” The main reason for the restriction is the substantial country-specific expertise required to convert local salaries to dollar equivalents.<sup>16</sup> In doing so, we exclude a growing minority of the WBG employees: the fraction of local hires increases from 7.4 percent to 37.8 percent over the time period of our data.

We make two minor additional sample restrictions. Among the 259,618 records corresponding to the universe of WBG headquarters employees between 1987 and 2015, we exclude the 4,689 records of executive directors and their staff, and of secondments (staff loaned and paid by other institutions). We also exclude a total of 229 records for which missing or anomalous grades were found (6 records), recorded gender changed over time (97 records), recorded salary was 0 (88 records), or recorded salary was clearly outside the grade range in the corresponding year (38 records).

# **2.2 Three Relevant Historical Trends**

Compensation and hiring practices have not remained static over the period of our data. In fact, multiple institutional changes and HR policies could have affected hiring and turnover as well as the salary structure. One advantage of our dynamic decomposition methodology is that it does not assume a stationary environment.

16Given the starting date of 1987 in our data, the dissolution of the Soviet Union and the emergence of local currencies, the creation of the euro replacing European currencies, as well as multiple spells of hyperinflation through the period of our data in countries ranging from Turkey to Ecuador all need to be addressed on a case-by-case basis. Although this salary conversion is possible, it lies outside the scope of the current project.

9