rafmacalaba/datause-encoder-data huggingface dataset:
of weak internal instruments in the SYS‐GMM estimator used in these papers. Using weak instrument‐ robust approaches to inference, I find that the data used in these papers are consistent with a wide range of both positive and negative values for the causal effect of inequality on growth. This indicates that, once the poor performance of the internal instruments used in the SYS‐GMM estimates of the benchmark specifications in these papers is properly accounted for, it no longer is possible to draw strong conclusions about either a negative or a positive effect of inequality on growth.

These findings in the benchmark specifications of these studies of course do not rule out the possibility that there may be other empirical specifications in which internal instruments are strong, or even if they are weak, that weak instrument‐consistent confidence sets are small enough to be able to draw interesting conclusions about the growth effects of inequality. Rather, these findings illustrate the importance of systematically documenting instrument strength in all applications of the SYS‐GMM estimator and relying on weak instrument robust approaches to inference where appropriate.

One key feature of the SYS‐GMM estimator is that the underlying identifying assumptions imply that a large number of lagged levels and differences of explanatory variables are available as instruments. This in turn implies that users of SYS‐GMM have a great deal of latitude to construct the instrument set from the multitudinous different possible combinations of these instruments, all of which are equally valid in terms of satisfying the relevant exclusion restrictions. This in turn raises the question of whether my conclusions about weak instruments hold not just for the instrument sets used in the benchmark specifications in these papers, but also across the many possible other instrument sets that could have been used instead. I take up this question in Section 4 of the paper, using the data set from Ostry, Berg, and Tsangarides (2014) as an illustration. Using this data set and a minimalist inequality‐ and‐growth specification, I systematically document instrument strength across a large number of alternative combinations of internal instruments. I find that weak instrument problems appear to be pervasive across these alternative instrument sets, and that virtually none of them support strong conclusions about a significant effect of inequality on growth, either positive or negative. This stands in stark contrast with the SYS‐GMM point estimates and t‐statistics, which suggest a very consistent pattern of conventional significance across all instrument sets.

The weak instrument problems that I document in this paper arise in a specific set of influential recent contributions to the inequality and growth literature. Moving beyond this particular application, my findings underscore the conclusions of Bazzi and Clemens (2013) on the importance of verifying instrument strength, and if necessary also relying on techniques that are valid when instruments are 4
WPS4137

# **How “natural” are natural monopolies in the water supply and sewerage sector?**

**Case studies from developing and transition economies***

Céline Nauges and Caroline van den Berg<sup>**1**</sup>

## **Abstract**

_We estimate measures of density and scale economies in the water industry in Brazil, Colombia, Moldova and Vietnam, four countries that differ substantially in economic development, piped water and sewerage coverage and characteristics of the utilities. We find evidence of economies of scale in Colombia, Moldova and Vietnam. In Brazil, we cannot reject the null hypothesis of constant returns to scale. The results of this study show that the cost structure of the water and wastewater sector varies significantly between countries and within countries, and over time, which has implications for how to regulate the sector._

### World Bank Policy Research Working Paper 4137, February 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._

> * We thank Antonio Estache, Serge Garcia, and Luis Alberto Andres for useful comments during the preparation of this paper.

> 1 Céline Nauges is a Senior Research Fellow at the French National Institute for Research in Agriculture (INRALERNA), University of Toulouse.  Caroline van den Berg is a Senior Economist at the Energy and Water Department of the World Bank. Corresponding author: Céline Nauges, LERNA-INRA, University of Toulouse, Manufacture des Tabacs, 21 Allée de Brienne, 31000 Toulouse, France. Tel: +33 5 61 12 85 17, Fax: +33 5 61 12 85 20, email: cnauges@toulouse.inra.fr.
# **Box 2: How much does procurement impact regulated costs in water and sanitation?**

One of the key decisions in organizing bids in the WSS sector is whether to bundle a treatment plant and a network component. The evidence from a sample spanning over 10 years (1997-2007) suggests that this decision impacted both bidder participation and bidding strategies. If works on a treatment plant was solely put out to tender, the average number of participating bidders was 4.4, and the relative bids averaged about 90% of the engineering cost estimate. Similarly, if only a network component was contracted out, about 5.8 bidders participated. Their bids were also about 90% of the expected cost, on average. However, when the two tasks were procured simultaneously under a single contract, the bidder participation dropped to about 3.3 firms. And the realized bids more than doubled (2.3 times the engineering cost).

There are two possible reasons for high costs of the bundling approach. First, the bundling might increase the entry costs of potential bidders and the resulting limited participation could further increase the equilibrium bid. This appears consistent with Fig. 1. Second, from the technical point of view, there may be no cost advantage for a firm to engage in the two different activities simultaneously. Therefore, the firms’ cost structure exhibits diseconomies of scope, i.e. being required to take on the two tasks as part of the procurement process may lead to higher costs which a regulator would have to recognize.

<!-- Start of picture text --> Figure 1: Levels of competition in ODA-financed water projects<br>(78 contracts between 1997 and 2007)<br>0.40<br>Mean = 5.2<br>0.35 Median = 4<br>0.30 Skewness = 1.2<br>Kurtosis = 3.5<br>0.25<br>0.20<br>0.15<br>0.10<br>0.05<br>0.00<br>2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21<br>Number of bidders<br>Source: Estache and Iimi (2011)<br>Fraction<br><!-- End of picture text --> An additional constraint on the effectiveness of the procurement process in the water sector is the concentration of the number of large players in the sector, and the fact that many of these large players enjoy the support of their governments keen to defend national champions as part of an industrial policy that increasingly open to the international diversification of risks. This concentration has an impact on the bargaining power of governments of countries with a much lower legal capacity to interact with operators in the context of conflicts for instance.

A recent study of local water contracts in France illustrates the institutional importance of this concentration nicely. Chong et al. (2015) show that municipalities differ in their ability to control the providers’ profits. They find that smaller municipalities (less than 10,000 inhabitants) pay a significant price premium for water provided by private operators as compared to those providers by public operators. There is no such premium for larger municipalities. Although there is no equivalent formal 24
government in power is right-wing (with left/center/uncoded as the complementary category). This is to capture the idea that right-wing governments may be more business-friendly and less willing to expropriate private foreign (or domestic) investors or bondholders. We also use constraints on the executive, to capture the idea that arbitrary seizures of property may be more difficult in a polity with greater checks on executive power.

**Table 2** begins by reporting the pure cross-sectional relationship between these variables and sovereign default and expropriation events, i.e. using cross-sectional averages over the entire sample period of all variables.<sup>6</sup> The sample consists of 126 developing countries where data on all variables are available, and is held fixed across specifications.  The first 12 columns report the simple univariate relationship between each of the six explanatory variables and the two types of sovereign theft.  Across countries in the long run, there is no significant relationship between the levels of debt and FDI outstanding and the likelihood that either will be expropriated.  As we shall see shortly, this long-run relationship is quite different from the short-run relationship, where high levels of debt are strongly correlated with subsequent default.  Columns (5) and (6) reveal that both types of sovereign theft are statisticallysignificantly less likely in countries with good policy.    Both types of sovereign theft are also significantly more likely to occur in slow-growing countries, as shown in Columns (7) and (8). Turning to the political variables, there is some evidence that right-wing governments are significantly less likely to expropriate.  However, government ideology is not significantly related to defaults in the cross-section of countries, nor is there evidence that executive constraints are significantly correlated with either type of sovereign theft.

Finally, columns (13) and (14) consider all the variables at once. Although the cross-country association between policy performance and expropriations now becomes statistically insignificant, the remaining findings are broadly similar to those in the bivariate regressions.

> 6 As noted above, sovereign default events last for multiple years in the Tomz and Wright (2010) dataset.  Our focus is on the onset of default episodes.  Accordingly, in the regressions in **Table 2** and **Table 3** , we construct a dummy variable that is equal to one for the first year of each default event, and is zero for all non-default-event years in the dataset (i.e. we drop observations corresponding to the second and subsequent years of the default event).  In **Table 2** , the dependent variable is the average over time of this dummy variable, while in **Table 3** we explore the annual variation in this variable.

11
**Figure 10: Current Account, Reserves, and Credit**

A. Current account balance and investment (% of <u>GDP), 1980 – 2004)</u> <!-- Start of picture text --> 15 50<br>10 40<br>5 30<br>0 20<br>-5 10<br>-10 0<br>1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004<br>Current Account Balance (LHS) Investment (RHS)<br><!-- End of picture text --> C. External debt as Percent of GDP and International Reserves <u>as Percent of Short-term Debt</u> <!-- Start of picture text --> B. International bank reserves (billion of US dollars)<br>and CPI Inflation (%)<br><!-- End of picture text --> <!-- Start of picture text --> 50<br>45<br>40<br>35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004<br>International reserves (billions of US$) CPI Inflation (%)<br><!-- End of picture text --> D. Long-term and Short-term External Debt (US$ Million) <!-- Start of picture text --> 80 450 110,000<br>70 400 100,000<br>90,000<br>60 350<br>80,000<br>50 300 70,000<br>40 250 60,000<br>50,000<br>30 200<br>40,000<br>20 150<br>30,000<br>10 100 20,000<br>- 50 10,000<br>1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004<br>0<br>Debt / GDP (%) (LHS) International reserves / Short-term debt (%) 1980 1981 1982 1983 1984 1985 Long-term 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 Short-term 1997 1998 1999 2000 2001 2002 2003 2004<br>E. Lending and Saving Rates of Commercial Banks, F. Credit Extended by Financial Institutions (Millions<br>January 1997 to January 2005 of Baht, 1988 Constant Prices), 1984 to 2004<br><!-- End of picture text --> <!-- Start of picture text --> 20<br>18<br>16<br>14<br>12<br>10<br>8<br>6<br>4<br>2<br>0<br>1997 1998 1999 2000 2001 2002 2003 2004 2005<br>Lending rates Savings deposits CPI<br><!-- End of picture text --> <!-- Start of picture text --> 5,500,000<br>5,000,000<br>4,500,000<br>4,000,000<br>3,500,000<br>3,000,000<br>2,500,000<br>2,000,000<br>1,500,000<br>1,000,000<br>500,000<br>0<br>1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004<br>Commercial banks Finance companies<br>Government Savings Bank Government Housing Bank<br>Bank for Agricuture and Agricutural Cooperatives Others<br><!-- End of picture text --> 25
# Types of Activities

21. The Brazilian government has defined the worst forms of child labor as activities involving the collection or production of charcoal, _sisel (/ute),_ cotton, vegetable products, sugar cane, tobacco, horticultural products, citrus, salt, flour, fish, wood, textiles, tiles or ceramics and activities related to the extraction of stones and gems. In addition, most harmful activities specific to urban areas include drug trafficking and prostitution, street vending (newspapers or other products), etc.

22. Boys' and girls' involvement in the worst forms of child labor varies by type of activities. As indicated in Table 6, rural girls comprise a higher proportion of working children in babacu and acai palm plantations, tobacco, and sisel (ute) farms, whereas rural boys are doniinantin sugar cane, cotton, fishing, and coal production.

**Table 6: Percentage of Working Children (10-14 years of age) in Rural Areas by Activity and Gender**

|AgriculturalActvity|Ru|ral|-Total|Ur|ban|Total|
|---|---|---|---|---|---|---|
||-Boys|GLrls||.<br>Boys|GLrls||
|Worstformns|||||||
|Cotton|1.2|0.3|1.0|0.2|0.0|0.1|
|_Agave/sisel_(ute)|0.0|0.3|0.1|-|-||
|Sugarcane|2.1|0.3|1.6|5.0|1.2|4.3|
|Tobacco|2.7|4.7|33|0.6|0.0|0.5|
|_Babacu(palm)_|2.4|6.4|3.5|-|-|-|
|_Acai(paln)_|16.7|20.6|17.8|9.2|9.8|9.3|
|Fishing|1.2|0.6|1.0|9.0|3.8|7.9|
|Coal|0.2|0.00|0.1|-|-||
|LessHarmful|||||||
|Corn|22.1|22.7|22.3|12.4|8.3|11.6|
|_Aipim_(sweetcassava)|11.0|11.1|11.0|6.3|8.4|6.8|
|Cattle|15.0|4.4|12.0|15.0|3.8|12.7|
|Poultry|2.2|10.5|4.5|11.9|36.5|16.9|
|Rice|8.1|4.2|7.0|7.0|3.8|6.4|

Source: Calculations based on PNAD, 1996 9
- 22 -

# **IV. DATA**

The sample data cover at maximum 136 countries that have exported beef and products to the EU market from 1990 to 2004.<sup>32</sup> The trade data come from _Intra- and Extra-EU Trade Statistics_ , which provide both quantity and value information on EU imports of “beef.”<sup>33</sup> The import values are deflated by the consumer price index in the region (1989=100). The average unit price is calculated by the deflated import value divided by quantity. Accordingly, the unit price is defined in terms of the ECU or euro per kilogram.<sup>34</sup> For conversion purposes, the period average exchange rates are used from the IMF _International Financial Statistics_ ( _IFS_ ).

Since the rate of customs duties varies across individual exporters, the paper assumes that the average most-favored-nation (MFN) tariff of beef products, which is estimated at about 200 percent (Morath, 1997), could apply for all countries that are not covered by the Cotonou beef protocol. By contrast, the beneficiary countries are supposed to enjoy zero in-quota tariffs—though not exactly zero even under the limit. Technically, there is another potentially level of tariff in the EU’s beef import market, because the EU offers the Generalized System of Preferences (GSP) as well as than the Cotonou protocol. However, since the utilization of the GSP has been limited (Rocha, 2003; Manchin, 2004), the final prices of beef products imported from non-beneficiary countries are simply assumed three times as high at the destination market as their customs prices.

The potential market size of European import beef is defined by the sum of beef imported by EU15 members from intra- and extra-region countries. To focus on examining the market access from outside regions, intra-regional imports are considered as an alternative option. It is noteworthy that the current analysis investigates a partial equilibrium in the sense that beef exporters outside the EU are supposed to compete with only themselves and intra-EU

> 32 In this analysis the EU market includes Austria; Belgium; Denmark; Finland; France; Germany; Greece; Ireland; Italy; Luxembourg; Netherlands; Portugal; Spain; Sweden; and the United Kingdom.

> 33 It includes fresh, chilled and frozen meat of bovine animals under category numbers 201 and 202.

> 34 The ECU is a basket of EU currencies, which was replaced with euro at a rate of 1:1 on January 1, 1999.
upon Articles _65-66_ of the Treaty of Paris (European Coal and Steel Community, ECSC), and make allowance for state aids permiitted under ECSC auspices.

# IV. Competition Laws and Institutions in the CEE countries

Five of the six CEE countries currently have competition legislation in force: Bulgaria, the Czech Republic, Hungary, Poland and the Slovak Republic.' To a greater or lesser extent CEE laws are modeled on the EU's approach to competition policy, distinguishing between collusive arrangements (Anticle 85), abuse of dominant positions (Article 86), and rules for mergers. All the Laws apply to goods and service markets (although some services are excluded in some jurisdictions), all appear to follow an 'effects doctrine' approach, and all are based on the conditional prohibition model. While many types of collusive arrangements appear to be prohibited on a _per se_ basis, in most cases exemptions are possible. Although superficially similar, there are substantial differences between the various law!. The discussion that follows draws upon the more detailed overview in Appidix 2.2 After the breakup of the Czech and Slovauk Federal Republic, the 1991 Federal competition law continued to be enforced in both countries. The Czech Republic adopted an amendment to the 1991 Federal law in November 1993, and a revised law is expected to be submitted to the Slovak Parliament in mid-1994. Until the Slovak Parliament adopts the draft legislation the Slovak Antimoopoly Office will apply the 1991 Czech and Slovak Federal law.

# _Substive discplines_

All the CEE laws prohibit cetain types of anti-conpetitive practices on a conditional basis. The Czech and Slovak law is the only one to contain an unconditional _per se_ prohibition on arrangements that violate legal norms of ethical behavior and on contracts that obstruct 'in a substantial way economic competition in a market." It provides an illustrative list of agreements that are prohibited (void) unless an exemption is granted by the competition authorities. Exemptions are automatic for an exhaustive list of tys of prohibited agreements if the authority makes no objection within two monhs of the receipt DIn Romamia work is ongoing on the drafting of an anttrust law. At the ime of writing the only laws to address some competition-related. issues are the 1991 Law on Unfair Compettion and the 1990 Law No. _15_ conceming rescauring of state economic units. The former incuds some prnrciples of free competition; the latter prohibits (on a _per se_ basis) certain practices, including price fixing (Chapter V, Association and Free Competition).

2 1Gray (1993) and Mastalir (1993) provide comp summaes of the anttrust legislation in the CEECs.

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