rafmacalaba/datause-encoder-data huggingface dataset:
2009; Du and Liu 2015; Gan, Guo and Xu 2017).<sup>9</sup> One of the reasons for this scarcity might be the difficulty in dealing with the selection bias in China’s privatization process. The slogan of the restructuring reform was to “grab the big and to let go of the small.” To “grab the big,” large and important SOEs were corporatized and consolidated; to “let go the small,” small and loss-making SOEs were mostly privatized. The government’s discretion and selection in the privatization process makes the evaluation of the causal impact of privatization complicated. To identify the causal effects of privatization in China, we explore exogenous factors in the political promotion mechanism that could be used to address the selection bias associated with privatizations.

In China there might be a strong link between local politicians’ promotion incentives and the privatization decision of local SOEs, which was under the control of the local government (Huang et al. 2017). Privatization entails significant costs for politicians, depriving their overt political connections with SOEs under their oversight, and therefore the associated control benefits. Moreover, privatization is usually followed by massive layoffs as part of the restructuring efforts, especially for the loss-making SOEs in this period. Indeed, between 1997 and 2002, over 27 million SOE workers, or about 27% of total SOE employment in 1997, had been laid off (Dong and Xu 2008). These layoffs would cost politicians some local support, though such support is not essential for their careers. On the other hand, privatization likely enhances corporate performance and thus delivers higher fiscal revenues and GDP growth (Chen et al. 2008; Bai, Lu and Tao 2009; Calomiris, Fisman and Yang 2010). Higher fiscal revenue and GDP growth likely boost the politician’s chance of promotion (Maskin, Qian, and Xu 2000; Li and Zhou 2005; Xu 2011; Shih et al. 2012; Persson and Zhuravskaya 2016). Thus, in deciding whether to privatize a local SOE, local politicians face the trade-off between the benefit of economic gains and the cost of local unemployment and of the loss of control benefits. At the time of financial losses of SOEs in the late 1990s, due to sharp drops in rent associated with SOEs, political resistance to privatizations under the Chinese political system should be much lower than in the democratic societies, and the importance of local politicians looms especially large for privatization decisions. In particular, local politicians younger than 58, 9 See in the introduction other references on privatizations, especially share issue privatizations, in China. `10`
it is collinear with the country-year and city fixed effects and cannot be estimated separately. However, a distance-specific transport cost elasticity can be calculated. Column 7 reports the coefficient of interest when _pt ∗ xi_ is replaced with _ln_ ( _pt_ ) _∗ xi_ . It is again negative and significant as expected. This can be translated into a distancespecific elasticity using three additional parameters: A simple regression of _ln_ ( _Pdiesel_ ) on _ln_ ( _Poil_ ) using the (Deutsche Gesellschaft f ̈ur Technische Zusammenarbeit, 2009) data for the fifteen sample countries provides an estimate of _εPdiesel,Poil_ = 0 _._ 6. Treating the Teravaninthorn and Raballand (2009) average fuel share as the marginal fuel share implies _ετ,Pdiesel_ = 0 _._ 35. Combining these estimates implies _εGDP,τ_ = _−_ 0 _._ 2 at the median distance from the primate, 439 km, and -0.4 one standard deviation (465 km) farther away. This calculation is meant to be illustrative, as it may suffer from several potential biases, including upward (toward zero) bias from substitutability of oil in the production of transport and downward (away from zero) bias from substitutability of transport in the production of city activity.

Country size varies dramatically within the estimation sample. For example, the farthest city in Sierra Leone is only 310 kilometers away from the primate, whereas in Mozambique, the farthest is over 2000 kilometers away. In order to ensure that not all variation is coming from the largest countries, column 8 shows a specification in which _ptxi_ is replaced by _ln_ ( _pt_ ) _ln_ ( _xi_ ).<sup>39</sup> The coefficient of interest is negative and significant.

The prices of commodities other than oil were rising in parallel with the oil price in this time period. It could be the case that country governments spent these commodity windfalls disproportionately near the primate city, either because it is easier for government officials to travel to project sites in cities near the capital, or because governments are more concerned with pleasing the residents of these cities. Table 4 reports results related to this potential effect. Column 1 reports the baseline specification on a sample restricted to the 58 percent of country-years for which national natural resource export income is available from WDI. Natural resource export income is defined here as the purchasing power parity (PPP) value of mineral and fuel exports. The coefficient of interest is still negative and significant, but larger in magnitude. Column 2 controls for the interaction between distance and the log of national natural resource export income. The coefficient of interest is essentially unchanged from column 1, and the

> 39The distance from the primate to itself is arbitrarily redefined as 1 kilometer in the log-log speci-

17
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17
strongly support our predictions if the sample included industrial countries.

The relationship between inflation and financial repression was discussed in section 2.2. Here we report the correlations between the financial-repression tax revenue and both inflation and changes in nominal exchange rates. As shown in figures 4 and 5, the correlations are all positive, except for the years 1984 and 1985. A comparison of the two figures seems to suggest that the revenue from financial repression is however more highly correlated with the change in the nominal exchange rate than with the rate of inflation.<sup>3 1</sup> Figures 6 and 7 report the scatter plot of the time-averages. The figures show the presence of two outliers: Mexico and Brazil. In the former country both inflation and the revenue from financial repression are very high; in the latter country the inflation rate is very high but the revenue from financial repression is lower than in the rest of the sample. The Mexico data cover the period 1984-1987, during which there were extensive trade and foreign exchange controls. The very high government revenues from financial repression in the last two years of this period follow the drop in oil prices in 1985. They are due to the substantial and largely unanticipated inflation and exchange-rate devaluation.<sup>3 2</sup> The Brazil data cover the period 1983-1987. They reflect the flexible exchange rate regime, as well as the sophistication of the country's financial markets.<sup>3 3</sup> The combination of ' gh inflation and low financial repression in Brazil is suggestive of the difficulties of rasing revenue from financial repression in countries where markets are relatively free and surprise exchange-rate devaluations are not possible. This

> **3 1 An issue we have not addressed directly is the correlation of financial repression wi h the** _real_ exchange rate, that is the nominal exchange rate corrected for the relative price levels. The reason for this omission is that, in the absence of short run "surprises" in exchange-rate changes, we have no strong theoretical priors about what **this** correlation should be. Of course, when exchange-rate surprises are taken into account, we expect **this** correlation to be high due to short-run price stickiness, and the fact that financial repression is correleted with the nominal exchange rate. Indeed, we have found that the year-to-year variation of financial repression is relatively highly correlated with the change in the real exchange rate. When we compute time-averages, we find that the cross-country correlation of financial repression and the change in the real exchange rate is about **30** percent-for both measures of revenue.

> 3 2 See Easterly (1989). He finds that the **total** tax on financial intermediation was 2 percent of GDP in 1985, an6i 9 percent in 1986.

33See, for example, Ghosh (1990) for a description of financial markets in Brazil.

18
_Table 1.2 Additional Employment Probability for the DTS, General Average HS Grade - Probit_ _Estimate on Current Employment_

|VARIABLES|(1)<br>Total|(2)<br>Total|(3)<br>Total|(4)<br>Total|(5)<br>Total|
|---|---|---|---|---|---|
|DTS dummy (=1, RP=0)||0.082**|0.062|0.042|0.039|
|||(2.053)|(1.539)|(1.014)|(0.934)|
|Standardized HS grade|0.039**|0.038**|0.042**|0.035*|0.121|
||(2.165)|(2.043)|(2.225)|(1.792)|(1.255)|
|DTS * std. HS grade|||||−0.047<br>(−1.183)|
|Years of schooling|0.003|0.002|0.002|−0.003|0.002|
||(0.255)|(0.203)|(0.205)|(−0.236)|(0.137)|
|Work experience|0.000|0.002|0.001|0.005|0.006|
||(0.071)|(0.503)|(0.291)|(1.191)|(1.240)|
|Work experience (squared)|−0.000|−0.000|−0.000|−0.000|−0.000|
||(−0.183)|(−0.500)|(−0.343)|(−1.231)|(−1.231)|
|Female|−0.118***|−0.140***|−0.124***|−0.106**|−0.105**|
||(−3.381)|(−3.599)|(−3.163)|(−2.465)|(−2.437)|
|Mother's education level|−0.002|−0.002*|−0.002**|−0.002**|−0.003**|
||(−1.530)|(−1.836)|(−2.195)|(−1.994)|(−2.409)|
|Observations|840|745|742|745|742|
|Enrollment Year dummy|NO|NO|YES|NO|YES|
|TVI dummy|NO|NO|NO|YES|YES|

_Source: DTS Tracking Survey, 2015, World Bank. World Bank calculations. Note: z-statistics in parentheses. * p<0.1; ** p<0.05; *** p<0.01_ 33
market up to the moment the SDCyC released its policy recommendations, it could not prove that oil firms engaged in any anticompetitive conduct.

**4. Independent refineries and wholesale market: market characteristics that make price competition more intense.**

In Argentina, there are seven refineries'<sup>4</sup> that produce more than 90% of the gasoline consumed in the country. All of these refineries were constructed before the deregulation and are owned by the incumbent oil firms. Given the size of the Argentine gasoline market, the capacity utilization rate (never exceeding 80%15) and the significant sunk costs (Scherer, 1996) involved in the construction of refineries, no new refinery was expected to be built for some years after deregulation. In fact, more than eleven years after deregulation no new refinery was built, although oil firms invested to upgrade the quality and production capacity of existing refineries.

When privatizing YPF, the Argentine government had the opportunity to sell a refinery with significant capacity (La Plata or Lujan de Cuyo) to an independent refinery (unbranded) or to a new entrant. What would have been the consequences of this option?. On the one hand, as mentioned in the previous section, it would have reduced the revenues obtained from the privatization of YPF and weakened its position as market leader. On the other hand, it would have reshaped the competitive scenario in the gasoline market. An unbranded refinery could have sustained the development of a wholesale gasoline market and the parallel emergence of jobbers, that is, wholesale agents that play a key role in competitive gasoline markets (Borenstein, 1996, 1997). The main role jobbers have in the American gasoline market -usually used as a benchmark for a competitive market- is to arbitrage between unbranded and branded refineries when feeding unbranded gasoline stations. The absence of jobbers or a well developed wholesale market has made the unbranded gasoline stations in Argentina too dependent on imports and on the willingness of the incumbent refining oil firms to sell them gasoline.

> **14** Lujan de Cuyo (RepsolYPF), La Plata (RepsolYPF), Dock Sud (Shell), Campana (Esso), Bahfa Blanca

> (EG3), Refinor (RepsolYPF, Pluspetrol and Perez Companc) and San Lorenzo (Perez Companc). **5** For sector specific statistics see http://energia.mecon.gov.ar/

14
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- 5 -

flows for the past 70 years, it has been found that the ARMA parameters—estimated with “goal programming”—are sufficiently accurate for projection purposes. Wong _et al_ . (2007), in the context of the Saugeen River in Canada, propose a more flexible technique, the semiparametric regression model, which imposes few restrictions on the disturbance processes.

Our VAR model includes two particularly important variables for hydrological forecasting: temperature and precipitation. There are many other input data that are potentially relevant to hydrology in a river, such as evaporation, soil moisture, catchment characteristics, land use, atmospheric circulation, polar ice, glaciers, and even human facilities and activities. Undoubtedly hydrological flows are complex phenomena. In order to keep our model simple and tractable, however, only temperature and precipitation are selected largely due to data availability, though there may be a sense that a bias exists in projected temperature and precipitation in many climate models (Bergström, 2001; World Bank, 2007).

The VAR model seems appropriate to examine hydrological data for three reasons. First, it is expected to uncover dynamic interactions among the variables of interest. The flow of a river is affected by regional climate, and vice versa. Both belong to the world water cycle. Second, hydrologic time series tends to exhibit a set of statistical properties necessary for VAR, such as stationarity (Salas, 1993; Koutsoyiannis, 2006). The fundamental assumption for estimating a VAR model is that the first two moments exist and are covariance stationary. Finally, it is computationally easy to perform.

The paper is organized as follows. Section II provides an overview of the three hydropower projects analyzed in the following sections. Section III describes the empirical model and data issues. Section IV presents the main estimation results. Demonstrating the climate change impacts calibrated from the hydrological models, Section V discusses some policy implications for preparing and operating hydropower projects.
102 Chaudhury and Morineau (1999: 8) 103 Steensgaard (1987: 142)

> 04 Chaudhury and Morineau (1999: 8)

105 Portuguese explorer who discovered the route to India (end of 15th century) and opened the sea route around the Cape of Good Hope.

10 Morineau (1999: 125) 107 Chaudhury and Morineau (1999: 3-4) 108 The Yuan (Mongol) pericid extended from 1279 to 1368 and the Ming period, from 1368 to 1644. 109 Information in this paragraph based on Ptak (1994: 35-44). 110 Frank (1998: 62) " Frank (1998: 84) 112 Frank (1998: 91) '13 Frank (1998: 62) 114 Maddison (2001: 97)

**1"5** Bairoch (1993: 88)

116 Maddison (2001: 115) '7 Desai (1971) as cited in EBairoch (1993: 89) 118 Bairoch (1993: 54)

**119** Maddison (2001: 116)

120 Bairoch states that more recent research shows that in some remote regions industrial activity survived for a long period so that the lower level of de-industrialization is probably more accurate (Bairoch 1993: 89-90). 121 Bairoch (1993: 90) 122 For "real income" he adjusts the figures for the differences in the purchasing power of currencies. His estimates are in 1960 US dollars and prices. 123 Bairoch (1993: 95-96) 124 Maddison defines the "drain" as "the colonial burden as measured by the trade surplus of the colony." In this way, he is attempting to "compare the colonial burden in the two countries as a share of their own national income, and the colonialist's gain as a share of their respective national incomes" (Maddison 2001: 87). 125 Maddison (1989: 645-64() 126 Maddison (1989: 646) 127 Tongzon (1998) 128 Pomeranz and Topik (1999) 129 Maddison (2001: 86) 130 Chia Siow Yue (1997) 131 Fan Gang (2000: 27) 132 Fan Gang (2000: 28) 133 The choice of regions is based on trade and investment partner relationships and is restricted by the limitations of time and space: in this paper.

134 See Table G. 1 in the General Appendix for a list of regional fora worldwide including their membership and date of inception.

135 Kawai and Takagi (2000: 12) 136 Numbers of tables and figures that begin with "S" are in the Statistical Appendix, those beginning with "G" are in the General Appendix and those starting with "H" are in the Historical Appendix.

137 These are consistent with indicators of economic size used by the World Bank. GNI measures the total domestic and foreign value a,dded claimed by residents. It comprises GDP plus net receipts of primary income (compensation of enmployees and property income) from nonresident sources. This was gross national product in previous editions of the World Development Indicators. GDP is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output. See World Bank (200 lb: 15) for an explanation of calculation methods and data sources.

138 ASEAN, APEC and other "regional institutions" are discussed in detail in Chapter III.

139 Brunei's ranking is not provided but is most likely a little higher than that of Singapore. The World Bank reports little data for Brunei and that which is reported is done so in a separate grouping (unranked) of small economies with populations between 30,000 and I million.

69