rafmacalaba/datause-encoder-data huggingface dataset:
important. If the allocation of firms for privatization is nonrandom, studies that do not adequately control for endogeneity will be biased.<sup>9</sup> This section reviews the empirical evidence concerning the impact of privatization on efficiency and welfare distribution and illustrates some of the issues mentioned above with examples drawn from existing empirical studies.

# **Firm Performance**

In the last few years, three excellent surveys reviewing the empirical evidence of privatization on firm performance have been published: Megginson and Netter (2001), Djankov and Murrell (2002), and Estrin et al. (2007). From our perspective, the strength of these surveys in comparison with similar papers is that they review the evidence while giving unique consideration to the methodological problems discussed above.<sup>10</sup> Megginson and Netter review 38 studies that examine the impact of privatization on the operating efficiency, ownership structure, or financial performance of former SOEs in developed and developing countries (including transition economies), as well as in competitive and noncompetitive markets, mostly utilities. They find that almost all studies of nontransition economies that examine postprivatization changes in output, efficiency, capital investment spending, and profitability document significant increases in these variables and significant decreases in leverage. The studies, however, are less unanimous with respect to the impact of privatization on employment. Some studies find significant increases; others, significant decreases; and still others, insignificant changes in employment following privatization.<sup>11</sup> A first example to illustrate the empirical evidence concerning the impact of privatization on efficiency is drawn from the wave of privatization of nonfinancial firms in Mexico during the period 1983–91 (La Porta and López-de-Silanes 1999). The authors include in their sample both

> 9 Gupta, Ham, and Svejnar (2000) present evidence of nonrandomness in privatization in the Czech Republic.

> 10  Other useful surveys are Kikeri and Nellis (2004) and Shirley and Walsh (2000).

> 11 According to Megginson and Netter (2001), the most compelling studies, taking into account sample size, coverage, and methodological rigor, are for nontransition economies: Galal et al. (1994); La Porta and López-deSilanes (1999); Dewenter and Malatesta (2001); and the three articles summarized in D’Souza and Megginson (1999). For transition economies the best studies (using the above criteria) are Dyck (1997); Weiss and Nikitin (1998); Claessens and Djankov (1999); Lizal, Singer, and Svejnar (2001); and Frydman et al. (1999).

10
The difference in mean growth between slum and nonslum children in 2013 is driven by differences in the mean levels of factors for slum and nonslum children, in particular, with respect to mother’s education attainment and household wealth. Similarly, the increase in mean growth between 2006 and 2013 for slum and nonslum children is driven by increases in the mean levels of factors, in particular, with respect to mother’s education attainment and household wealth.

There is fairly consistent international evidence on the large positive effect of mother’s education on child growth. For example, using microdata for a large set of developing countries, Alderman and Headey (2017) find that the effect of mother’s education on child growth increases with years of education, is larger than the effect of father’s education, and is larger for countries with high stunting rates. Maternal education is theorized to affect child nutrition status through a household income effect arising from greater labor earnings, which we attempt to control for based on household asset-based wealth. Maternal education is also theorized to affect child nutrition status through the direct delivery of health and nutrition information; delayed age of marriage and age at child’s birth; greater ability to acquire, absorb, and apply health and nutrition information from other sources; greater openness to RMNCH services; greater decisionmaking authority within the household with respect to food, health, and care; and access to more-educated social networks (Ruel et al. 2013). Using data from a slum settlement in Dhaka, Fakir and Khan (2015) find that the effect of mother’s education attainment on child underweight status appears to be partially mediated through her knowledge of health-promoting behaviors. Our data do not allow us to test potential pathways. Nevertheless, the results suggest that policies and programs that aim to raise girls’ education attainment are appropriate, and should receive greater priority.

Likewise, international evidence is fairly consistent in showing a large positive effect of household economic status on child growth (Ruel et al. 2013). Cash transfers offer one way to raise household income. Manley, Gitter, and Slavchevska (2013) find that, while the collective evaluative evidence of both unconditional and conditional cash transfer programs is mixed in developing countries, the aggregate effect size of these programs on child growth is small and insignificant. However, the study indicates that the transfers may have a larger impact on poorer, younger, and more socially disadvantaged children; on children in settings with relatively poor nutrition status or low health service utilization rates at baseline; and on children in households 33
In this essay, we evaluate the experience with health insurance in LMICs over the last 20 years, where health insurance is provided by a specific scheme that is additional to the subsidized care available through public clinics. We start by documenting the transition to health insurance drawing on data from 100 Demographic and Health Surveys across 62 countries between 1989 and 2019. Then, using countrylevel examples and a review of existing evaluations, we describe how governments have structured their health insurance schemes and how these schemes have functioned in practice. Our conclusion from this review is that health insurance schemes have successfully increased financial protection and utilization but there is (yet) little evidence of improvements in health outcomes and little demand for health insurance among households, even when it is heavily subsidized.

Motivated by this review, we discuss—and rule-out—the possibility that health insurance has not improved health outcomes because of systemic constraints in the delivery of health care. Instead, we believe that health insurance triggered behavioral responses among providers that have systematically undermined the objectives of insurance schemes. These responses have led to prices that are higher than those mandated under the program, an increase in unnecessary care, and new sources of uncertainty as insured patients do not know whether the insurance will be honored or whether they will be correctly treated.

While such behavioral responses (sometimes called “provider moral hazard”) are also a concern in highincome countries, health insurance schemes typically work with a variety of institutions that seek to curb these forms of physician excess, including review boards, professional norms, public reporting, and punitive enforcement through courts.<sup>3</sup> In LMICs however, non-price incentive systems are poorly developed and have not been used successfully in combination with health insurance schemes, often creating social tensions in which patients take matters into their own hands: as one example, there were an estimated 17,000 attacks and agitations against doctors in China in 2010 alone (Tussing, Wang, and Wang 2014).

We conclude that the first twenty years of experience with health insurance schemes in LMICs shows that it is impossible to divorce the quality of care that health insurance offers from the financial protection it

> 3 For examples of provider moral hazard in a US context, see Gruber and Owings (1996) on the use of C-sections, Baker (2010) on how doctors prescribe more magnetic resonance imaging after buying an MRI machine for their clinic and, Clemens and Gottlieb (2014) on how treatment choices depend on reimbursement rates.

3
Table 4 shows that out of nearly 32,000 individual users, 76 percent report complaints about only one municipality; 12 percent report complaints about two municipalities. The remaining 12 percent report complaints about three or more municipalities. These results indicate that most users are concerned about potholes in only one municipality, presumably their residence.<sup>18</sup> Sixth, if the instrumental variable is not randomly assigned across the municipality-temporal cluster, the exclusion restriction is violated, and our estimates will be biased and inconsistent. To test for this potential violation of exclusion restriction, we perform a balancing test by regressing our instrumental variable on a number of time-varying geophysical, economic, and social indicators disaggregated at the municipal level, which we collected from the municipal statistics website of the Russian Federal State Statistic Service, ROSSTAT.<sup>19</sup> Appendix Table A.6 shows that none of the estimated coefficients of indicator variables came up as statistically significant, rejecting the nonrandom assignment hypothesis.

Finally, our estimates could be biased if they are confounded by potentially omitted political preferences of _Rosyama_ and _Nash Gorod_ users. Because _Rosyama_ is the political opposition project, one could assume that the complaints made through that application would concentrate in municipalities less likely to vote for the incumbent Moscow mayor. To test this hypothesis, we perform a balancing test of online platforms by regressing the share of complaints made through _Rosyama_ in 2013 on electoral competition measures.<sup>20</sup> Appendix Table A.7 shows the results of the balancing test. The share of complaints made through _Rosyama_ does not seem to result in a statistically significant difference in any of the three measures of electoral competitiveness we employ, rejecting the hypothesis of user selection bias.

# Discussion

The main results of our analysis support hypothesis (H1) about the positive political effects of digital public engagement on the issue of road quality in Moscow. Moscow city authorities have actively invested in participatory mechanisms of local governance. Our examination of digital means of ensuring road quality in Moscow reveals that the higher engagement with these governance

> 18 Unfortunately, neither of two online platforms shows the address of the reporting user.

> 19 Source: <u>https://rosstat.gov.ru/munstat, [last accessed: September 2020].</u>

> 20 We focus on 2013 because this was the year when both platforms had roughly equal shares of complaints. Since then, the share of total complaints made through _Rosyama_ has drastically fallen and, even if bias was present, unlikely to make any significant effect on estimated coefficients.

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# **5. Baseline Results**

The high cost of financial intermediation in Brazil in absolute terms, and in comparison to other countries, is a key source of policy concern. The difference between bank lending and deposit interest rates measured by the IFS spreads illustrates that Brazil has one of the highest interest spreads in the world, well above 30 percent in 2009 (see Figure 2).

**Figure 2. Link between IFS and SELIC rate is weak but link between NIM and SELIC rate is strong**

<!-- Start of picture text --> 70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009<br>NIM Actual SELIC Rate IFS<br>Percentage points<br><!-- End of picture text --> _Source_ : Banco Central do Brasil, BankScope and IMF (IFS); Note: NIM vs. SELIC Rate The high cost of intermediation, as measured by the IFS spreads, has been reduced considerably in Brazil from 58.4 percent in 1998 to 35.4 percent in 2009 (Figure 2). However, the IFS spread remains very high compared to other countries as well as compared to the SELIC rate (the official BCB rate), which has declined to less than 10 percent in 2009 (Figure 2). Brazil experienced very high inflation incidents in the past but has successfully brought inflation under control. Nevertheless, there has not been a sufficient reduction in interest spreads to moderate levels even as the fiscal and monetary environment has improved in recent years.

Improving the performance of the financial system is a main concern for development policy in Brazil because it is inhibiting investment and growth despite the impressive performance of the Brazilian economy. In that vein, there has been a substantial amount of policy and academic research in recent years led by the BCB and others. There were two important studies done to address these issues, the first by Afanasieff, Lhacer and Nakane (2002) and the second by de la Torre, et al. (2006). Despite the insights provided by the studies there remains considerable disagreement as to which methods should be used to tackle the issue and to the nature and causes of the high spreads in Brazil. Our paper attempts to separate the spreads into the macro and micro components.

De la Torre, et al. (2006) first established a link between the SELIC rate and interest spread. They calculate the adjusted SELIC rate measured by multiplying the SELIC rate with one minus the probability of default. Then macroeconomic variables are used as explanatory variables to explain the 13
# <u>Table 5: Sample Split by Firm Legal Status</u>

||<br>(1)<br>Unincorporat|(2)<br>ed business|(3)<br>Incorporated|(4)<br>business|(5)<br>Unincorpora|(6)<br>ted business|(7)<br>Incorporate|(8)<br>d business|
|---|---|---|---|---|---|---|---|---|
|Variable|OLS<br>License|2SLS<br>License|OLS<br>License|2SLS<br>License|OLS<br>Payroll|2SLS<br>Payroll|OLS<br>Payroll|2SLS<br>Payroll|
|Payroll registry|0.118**|0.289|0.0233|-0.316|||||
||(0.0478)|(0.228)|(0.0373)|(0.315)|||||
|License|||||0.139***|0.483*|0.0480|2.422|
||||||(0.0528)|(0.253)|(0.0556)|(2.470)|
|Log distance to SUNAT|-0.142***|-0.138***|-0.0272|-0.0402|||||
||(0.0351)|(0.0353)|(0.0210)|(0.0253)|||||
|Firms in E-Payroll / firms in SUNAT|||||0.026***|0.026***|0.016**|0.033|
||||||(0.007)|(0.007)|(0.007)|(0.023)|
|Log product per worker|0.0425|0.0260|0.00794|0.0135|0.104***|0.0839**|0.0196|-0.00725|
||(0.0286)|(0.0357)|(0.0173)|(0.0191)|(0.0301)|(0.0342)|(0.0209)|(0.0529)|
|Log number of workers|0.124***|0.0941*|0.0492***|0.0719***|0.183***|0.141***|0.0579***|-0.0583|
||(0.0366)|(0.0537)|(0.0167)|(0.0274)|(0.0382)|(0.0496)|(0.0202)|(0.128)|
|Age 5-8|-0.00893|-0.0420|0.0723*|0.0445|0.188**|0.183**|-0.0933*|-0.264|
||(0.0706)|(0.0824)|(0.0399)|(0.0496)|(0.0736)|(0.0761)|(0.0486)|(0.206)|
|Age 9-12|0.167**|0.125|0.0434|0.0268|0.209***|0.149*|-0.0575|-0.151|
||(0.0719)|(0.0899)|(0.0434)|(0.0487)|(0.0750)|(0.0886)|(0.0528)|(0.149)|
|Age 13-16|0.186**|0.170**|0.114**|0.0684|0.0766|0.00797|-0.129**|-0.388|
||(0.0835)|(0.0855)|(0.0453)|(0.0640)|(0.0884)|(0.104)|(0.0552)|(0.294)|
|Age 17-+|0.213***|0.173**|0.180***|0.150***|0.194**|0.116|-0.0791|-0.501|
||(0.0716)|(0.0883)|(0.0445)|(0.0546)|(0.0753)|(0.0957)|(0.0550)|(0.454)|
|Constant|0.547|0.695|0.660**|0.816**|-1.467***|-1.533***|0.0741|-1.839|
||(0.516)|(0.549)|(0.289)|(0.339)|(0.556)|(0.576)|(0.379)|(2.150)|
|Observations|391|391|497|497|391|391|497|497|
|R-squared|0.215|0.188|0.089|-0.068|0.178|0.084|0.068|-3.474|
|Weak identification test||17.06||7.77||18.26||1.13|

_Note:_ Standard errors are in parentheses. Significance: *** p<0.01, ** p<0.05, * p<0.1. Stock-Yogo weak ID test critical values: 16.38 (10% maximal IV size); 8.96 (15% maximal IV size).

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- 73 -

In all countries the formal systems have been relatively successful as well, and, as will be discussed below, became increasingly differentiated in function and governance from the nonformal system.

In the middle and later stages of systems development all three countries invested in larger numbers of institutions, more modes, and the development of policy and management capacity.

In sum, the record suggests that by beginning with relatively small investments in formal institutions, and gradually increasing the complexity of development in terms of the variety of modes. As policy, planning and management capacity developed, these countries were able to build incrementally from experience.

(d) Responsive Planning: In general, these systems were planned in response to -- not in anticipation of -- employment demand. In early stages, manpower data and manpower forecasting capacity were largely absent. Investments were justified on the basis of demonstrated industrial expansion. The development of strong institutional linkages between training and employment to facilitate incremental and localized planning and adjustment were, in retrospect, important alternatives to formalized manpower forecasting. In this context, the location of training institutions became an important variable. In Korea sites were chosen to be close to expanding enterprises; in Brazil, mobile training units were created to take training to the trainees.

(e) Early and Sustained Involvement of Enterprises: In all three countries sustained efforts were made to establish linkages between training and employment for all modes (in Brazil, these linkages had been part of the SENAI tradition since the 1940s). Enterprises played active roles in curriculum and enrollment decisions and in the design and provision of on-the-job training experience and apprenticeships. What may be most important is the consistency of commitment in training agencies to the importance of these linkages. Combined with expanding employment and increasingly effective enterprise management, this helped create a supportive "ethos" in which the needs of employers were taken seriously and reflected in training plans and curricula.

In later stages, the nonformal systems began to branch out to provide a range of training services to enterprises. In Jordan, this has taken the form of training centers established with the assistance of the Vocational Training Corporation in large enterprises, and in assisting groups of small enterprises to jointly sponsor apprentices for VTC training. In Korea and Brazil the nonformal training agencies have as a matter of policy sought to help enterprises develop their own training capacity.

(f) Evolution of Policy and Management Capacity to Match System Complexity: Each country began with relatively strong management capacity in Ministries of Education, but relatively undeveloped
real exchange rate depreciations and capital outflows relative to the cases of no policy and no learning. This is because agents are less uncertain about the future and save less for precautionary reasons. When this mechanism is strong enough, imposing capital controls could result in welfare losses relative to the decentralized equilibrium.

The key assumption in my model is that people learn about economic fundamentals from capital controls. In the empirical section, I provide some evidence of this assumption from an event study of capital control announcements in Brazil and from an exercise nowcasting Brazilian real GDP. Event studies using high-frequency data show that expectation of economic fundamentals in Brazil respond meaningfully to major capital control announcements. Specifically, I use daily survey data of market participants’ median expectation of quarterly real GDP growth collected by the Central Bank of Brazil and I consider six major capital control announcements in the country between 2008 and 2013. On average, a tightening(loosening) announcement is associated with a downward(upward) revision of real GDP growth forecast of 0.23%.

Since the survey data averages many forecasters’ expectations constructed with different methodologies, and hence can be hard to interpret in greater details, I provide a second set of empirical evidence by taking a stand on how to form expectations of fundamentals. Specifically, I put myself in the position of a forecaster who employees a commonly-used econometric model and uses all types of available macroeconomic data to produce nowcasts<sup>3</sup> of Brazilian quarterly GDP growth rates in real-time. Including capital control announcements in the forecaster’s information set helps improve the precision of her nowcast. The magnitude of such improvement measured in the nowcasting model provides a basis for the calibration of key model parameters related to Bayesian updating and learning in my quantitative model earlier.

# **2 Literature Review**

This paper contributes to several strands of the international macroeconomics literature. First, it adds to the recent theoretical literature of macro-prudential policies and 3A nowcast is a forecast of the present or the very-near future when data have yet to be released.

3
BURKINA FASO’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE The second factor is the widespread practice of truck overloading, a factor that is endogenous to the system and reflects a lack of institutional capacity—not only in Burkina but also among its neighbors— to enforce regulation and good governance practices. As the Burkinabè trucking market is regulated through the ―tour de role‖ system, which caps cargo loads and truckers’ revenues, transport providers seek to maximize their revenues by bribing freight bureaus, customs officers, and police to allow overloaded vehicles (World Bank 2009b). Needless to say, overloading exerts considerable wear and tear on the infrastructure itself. The solutions for monitoring overloading, however, are far from straightforward, particularly because part of the control should be first exercised at freight-origination points (that is, ports) rather than en route (where it is more difficult to penalize and requires regional agreements). Given the competition among ports, this approach should be coordinated between Dakar, Abidjan, Lomé, Cotonou, and Accra, and should be applied with the same rigor in each of the freightorigination points. In the current situation, a stricter application in Lomé would immediately divert traffic from landlocked countries toward Accra, especially as Ghanaian transporters are apparently those who load the most (World Bank 2007).

With all these factors put together, Burkina were to eventually fund road maintenance fully via the fuel levy collected, the levy would need to be very high—on the order of 20–30 cents per liter of gasoline consumed (figure 8)—a rate by all means unaffordable for most of the Burkinabè domestic users.

But what are the alternate sources of maintenance resources? The obvious answer is transfers from the central government, that is, increased funding from taxpayers in general. The existing level of capital spending for the road sector—at less than 1 percent of GDP—is low by regional standards (figure 9). This suggests that even

**Figure 8. Spending requirements in Burkina Faso are the thirdhighest in the region vis-à-vis traffic levels**

<!-- Start of picture text --> 60<br>50<br>40<br>30<br>20<br>10<br>0<br>Optimal for maintenance Optimal for maintenance<br>and rehabilitation<br>Source: Gwillliam and others 2008.<br>US cents/liter<br><!-- End of picture text --> in the context of Burkina, which is characterized by small state revenue and a high reliance on external aid, there is some room to increase the allocation of resources to roads without creating any major unbalance in the fiscal coffer.

16