rafmacalaba/datause-encoder-data huggingface dataset:
|(7)<br>(8)<br>Perception<br>index<br>Perception<br>index|0.061**<br>(0.031)<br>0.067<br>(0.044)<br>-0.001<br>(0.001)|0.494<br>0.494<br>0.018<br>0.018<br>277<br>153|, hypothetical use, and<br>pplic. is a dummy that<br>the number of cases the<br>applic. is a dummy that<br>e number of employees,<br>p_<_0.10, ** p_<_0.05, ***|
|---|---|---|---|
|(6)<br>Hypothe-<br>tical|0.136**<br>(0.067)|0.750<br>0.026<br>139|n and costs<br>ter decree a<br>rols include<br>fter decree <br>l for baselin<br>as follows: *|
|(5)<br>Hypothe-<br>tical|0.052<br>(0.055)<br>0.003**<br>(0.002)|0.750<br>0.017<br>251|ved duratio<br>, Case(s) af<br>cation. cont<br>case, Case a<br>odels contro<br>re denoted|
|(4)<br>Costs (in<br>1000<br>FCFA)|-8.052<br>(238.308)|1140.051<br>0.138<br>151|on percei<br> is all frms<br>decree appli<br>d only one <br>cree. All m<br>nce levels a|
|(3)<br>Costs (in<br>1000<br>FCFA)|260.672<br>(222.757)<br>6.487<br>(8.243)|1140.051<br>0.085<br>272|the reform<br>ols: sample <br>case after<br>rms that ha<br>n of the de<br>S. Signifca|
|(2)<br>Duration|-0.919<br>(2.717)|21.508<br>0.053<br>152|impacts of<br>. Uneven c<br>at least one<br>tricted to f<br> introductio<br>ated by OL|
|(1)<br>Duration|Case(s) after decree<br>1.504<br>applic.<br>(2.172)<br>Case after decree<br>applic.<br>Number of cases<br>-0.021<br>(0.094)|Pre-mean<br>21.508<br>R-Squared<br>0.003<br>Observations<br>275|Notes<br>: Estimates of frm-level <br>perception of the justice system<br>takes value one if a frm has had<br>frm had. Even cols: sample res<br>indicates the case was after the <br>include a constant, and are estim<br>p_<_0.01.|

47
to raise the official poverty line were being seriously considered within the Government of China.) In estimating China’s poverty rate using the international poverty lines our estimation methods follow Chen and Ravallion (2004, 2007). We focus initially on household consumption expenditure as the welfare indicator for measuring poverty. This follows our past practice in measuring global poverty. However, we also report results for income poverty measures, which are more common in poverty analysis for China.

We readily acknowledge that the sense in which the old and new poverty lines can be meaningfully compared is rather limited, given that so much has changed (as we have emphasized above). However, it is a natural to ask what the combined effect of all our changes has been. (The underlying distributional data are the only thing that has not changed, beyond updating the series to 2005.) Table 1 gives estimates using both the old (1993) PPP and two new poverty lines. One of these lines simply updates the 1993 line for inflation in the US ($44.25 per month). However, as noted above, this gives a poverty line that is well above that found in the poorest countries (due to some combination of a failure of the PPP principle to hold and non-comparabilities of the two sets of PPPs). So we also give results for a 2005 poverty line of $38 per month, as proposed by Ravallion et al. (2008), which is the mean poverty line for the poorest 15 countries (based on Figure 2), and $60.83 per month ($2 a day) which is about the median ($60.81) of 75 countries’ national poverty lines used by Ravallion et al. (2008). The “adjusted” estimates assume that the urban price level facing the poor is 37% higher than in rural areas. Figure 4 plots the estimated poverty rates over time using both the $32.74/month ($1.08/day) line based on the 1993 PPP and the $38/month ($1.25/day) line, with and without our correction for the sampling bias in the 2005 ICP price data.

As expected, there is a marked upward revision to the estimated poverty count for China, though the marked decline over time in the poverty rate remains evident. Indeed, the new PPP suggests an even larger absolute reduction in the poverty rate since 1981. Using our corrections for sampling bias in the ICP data for China, and our new international poverty line of $1.25 a day in 2005 prices, the poverty rate fell by 68 percentage points over 1981-2005, as compared to 58 points using our previous “$1 a day” line based on the 1993 PPP.

10
premium between Rs. 80 and Rs. 120 ($2-3 US).<sup>4</sup> A policy covering all three phases (column “Combined Premium”) costs Rs. 260 to Rs. 340 ($6-8 US), including a Rs. 10 discount. IFFCOTokio policies are based on cumulative rainfall over the entire monsoon season (defined as June 1 to August 31) at government rainfall stations. Policy premiums are lower, between Rs. 44 and Rs. 86, reflecting a commitment to make policies accessible to even the poorest households. Households in both regions were free to purchase any whole number of policies as desired.

Each insurance contract specifies a threshold amount of rainfall, designed to approximate the minimum required for successful crop growth. As an example, the Phase I ICICI Lombard policy in Mahbubnagar pays zero when cumulative rainfall during the 35-day coverage phase exceeds the strike of 70mm. Payouts are then linear in the rainfall deficit relative to this threshold, jumping to Rs. 1000 when cumulative rainfall is below the exit of 10mm, meant to correspond approximately to a point of crop failure. IFFCO-Tokio policies have a similar structure, paying out whenever rainfall during the entire monsoon season is at least 40% below a specified average level for that district (normal rain).

The exception to this basic structure is the Phase III ICICI Lombard contracts, which cover the harvest period. These pay off when rainfall is excessively high, rather than excessively low, to insure against flood or excess rain that damages crops prior to harvest.

_Marketing and sales. –_ Microfinance institutions or non-government organizations (NGOs) typically sell rainfall policies on behalf of insurance companies, and handle payout disbursals. An important advantage of rainfall insurance is that payouts are calculated automatically by the insurer based on measured rainfall, without households needing to file a claim or provide proof of loss. This significantly reduces administrative expenses.

In Andhra Pradesh, insurance is sold to households by BASIX, a microfinance institution with an extensive rural network of local agents known as Livelihood Services Agents (LSAs). These LSAs have close, enduring relationships with rural villages and sell a range of financial services including microfinance loans and other types of insurance. In our Gujarat study areas, rainfall insurance is marketed by SEWA, a large NGO that serves women.

_Actuarial values, observed payouts and pricing. –_ For four policies in Table 1, we are able to calculate a measure of expected payouts using historical rainfall data. In each case, we

> 4 As a point of reference, the average daily wage for agricultural laborers in our survey areas at the time of the study is around Rs. 50, although incomes for landed farmers or more skilled workers are significantly higher.

6
seasonal precipitation observed in each county over the period of interest is calculatde to generate a time-invariant climatic variable. The climatic index is constructed as the mean of both variables, and denote this index _Climvp_ for village _v_ in province _p_ .<sup>10</sup> Second, the analysis utilizes a FAO-generated index of agronomic suitability for highinput irrigated rice. This index is time-invariant, and is calculated for each sampled locality as the mean value observed within the borders of the county in which the locality lies, denoted _FAOvp_ .

It is important to clarify the level at which both indices vary. The variables of interest ( _Climvp_ and _FAOvp_ ) are constructed using the geographic coordinates reported for the county in which each village lies, given that this is the lowest level at which linkable geographic indicators are reported for this dataset; village-level geocoding information is not publicly available. However, in this sample, cross-county heterogeneity is virtually equivalent to cross-village heterogeneity, as only one village is sampled per county.<sup>11</sup> The underlying variation for the climatic index is drawn from geo-coded data reported by 730 weather stations across China. To take into account spatial correlation in climatic characteristics, the standard errors in all subsequent specifications will be estimated employing two-way clustering at the province and year level, to allow for arbitrary correlation in the climatic index across observations in the same province.<sup>12</sup> The relationship of interest between climatic conditions and quota quantity can be estimated by regressing quota quantity on these climatic indices, conditional on provinceyear fixed effects; in addition, the direct correlation between quota quantity and rice area is estimated. Quota quantity for household i in village _v_ , province _p_ , and year _t_ is denoted _Qivpt_ ; area cultivated in rice is denoted _Aivpt_ ; and province-year fixed effects are denoted

> 10Precipitation is re-scaled to have the same mean as total temperature. The top and bottom 2% of climatic index observations are trimmed to minimize the of outliers.

> 11There are two pairs of villages located in the same county in the core sample.

> 12More specifically, standard errors are estimated employing the ivreg2 command in Stata and the two-way clustering option.

12
||P<br>Title|PR Working Paper Series<br>Author|Date|Contact|
|---|---|---|---|---|
|WPS81|Reaching People at the Periphery:<br>Can the World Bank's Population,<br>Health, and Nutrition Operations<br>Do Better?|Rlchard Heaver|September 1988|<br>S. Ainswort<br>31091|
|WPS82|Microeconomic<br>Theory of the House-<br>hold and Nutrition Programs|Dov Chernichovsky<br>LindaZangwill|September 1988|<br>S. Ainsworth<br>31091|
|WPS83|Welfare Costs of U.S. Quo+as In<br>Textiles, Steel, and Autos|Jaime de Melo<br>David Tarr|September 1988|<br>C. Cabana<br>61539|
|WPS84|Black Markets for Foreign Exchange,<br>Real Exchange Rates and Inflation:<br>Overnight vs. Gradual Reform in<br>Sub-Saharan<br>Africa|Brian Pinto|September 1988|<br>R. Blade-Chare<br>33754|
|WPS85|Wage Responsiveness<br>and Labor Market<br>Disequilibrium: Exploring the<br>Components<br>of Open Unemployment|Ramon E. Lopez<br>Luis A. Riveros|||
|WPS86|External Balance, Fiscal Policy and<br>Growth in Turkey|Ritu Anand<br>Ajay Chhibber<br>Sweder van Wijnbergen|||
|WPS87|Vocational and Technical Education<br>in Peru|Peter R. Moock<br>Rosemary T. Bellew|||
|WPS88|Costs, Payments, and Incentives In<br>Family Planning Programs|John A. Ross<br>Stephen L. Isaacs|September 1988|S. Ainsworth<br>31091|
|WPS89|Export Quota Allocations,<br>Export<br>Earnings and Market Diversifications|<br>Taeho Bark<br>Jaime de Melo|September 1988|C. Cabana<br>61539|
|WPS90|A Framework for Analysis of Mineral<br>Tax Policy in Sub-Saharan<br>Africa|Robert F. Conrad<br>Zmarak M. Shalizi|September 1988|A. BhalIla<br>60359|
|WPS91|<br>Israel's<br>Stabilization<br>Program|Nissan Liviatan|September 1988|N. ilviatan<br>61763|
t+2. So over the two periods, Phoenix Miracles are those firms that had ΔS > 0 with ΔL1 ≤ 0. In Panel B2, we define external financing by changes in short-term borrowing, long-term borrowing, net capital stock issuance, and net cash flow from other financing activities.<sup>18</sup> So we have: where ΔLTDt+1 and ΔLTDt+2 are the net changes in long term borrowing reported on the cash flow statement at t+1 and t+2, respectively, ΔCSt+1 and ΔCSt+2 are the net capital stock issuances reported on the cash flow statement at t+1 and t+2, respectively, and ΔOFINt+1 and ΔOFINt+2 are the cash flows from other financing activities at t+1 and t+2, respectively.

Panel B1 of Table 3 shows that across the 5 countries in our sample, the percentage of firms that can be classified as Phoenix Miracles varies from 7.89% in Mexico (identified as a Macro miracle but not a Micro miracle since there was no recovery in aggregate sales from t to t+2) to 45.33% in Korea (a Micro miracle but not a Macro miracle). Across the 5 3S episodes, we find that only 37.03% of the firms can be classified as Phoenix Miracles, thus suggesting that less than half the sample can be classified as miracles since they recovered in the absence of short-term borrowing. Of the remaining we find that 19.61% of the firms had a recovery in sales and short-term borrowing, 13.20% had no recovery in sales but a recovery in short-term borrowing (suggesting that these firms may have faced a demand shock), and 30.17% of the firms had no recovery in either sales or short-term borrowing.

Panel B2 shows that when we expand the definition of external financing, the percentage of Phoenix Miracles across the 5 episodes drops to 30.44% (from 37.03% in panel B1). The largest percentage of Phoenix Miracles is 41.76% in Thailand (identified as both a Macro and Micro Miracle), but even here, the percentage of Phoenix miracles drops from 44.69% when we define external financing narrowly as short-term financing, to 41.76% when we define external financing to also include long-term borrowing, capital stock issuance and other financing activities. While the percentage of Phoenix Miracles goes down, the percentage of firms that had a recovery in sales and credit goes up by the same amount as expected. Furthermore, with this

> 18 In Bloomberg, cash flow from other financing includes any financing activities not already included as a portion of Dividends Paid, increases/decreases in short-term borrowing, increases/decreases in long-term borrowings, increases/decreases in capital stock. It includes foreign exchange adjustments, changes in minority interests, and financing costs.

16
Couture, Toby D.; Cory, Karleen; Kreycik, Claire; Williams, E.; 2010. A Policymaker‟s Guide to Feed-in Tariff Policy Design, NREL, http://www.energy.eu/publications/A_Policymakers_Guide_to_Feedin_Tariffs_NREL.pdf DB Climate Change Advisors, 2010 Global Energy Transfer Feed-in tariff for Developing countries. New York: DB Climate Change Advisors.

Ecofys 2008 Policy instrument design to reduce financing costs in renewable energy technology projects, Ecofys International BV Greacen, Chris, Norbert Kahyoza, Anastas Mbawala (2010) Towards Light Handed Regulation for Small Power Producers in Tanzania, draft, World Bank and PPIAF.

International Energy Agency/ OECD; 2008. Deploying Renewables: Principles for Effective Policies, IEA/OECD, Paris, France.

Lesser, Jonathan; Su, Xuejuan; 2008. Design of an Economically Efficient Feed-in Tariff Structure for Renewable Energy Development, Energy Policy, Vol. 36, 981-990.

Lipp, Judith; 2007. Lessons for Effective Renewable Electricity Policy from Denmark, Germany and the United Kingdom. Energy Policy, Vol. 35, 5481-5495.

Meier, Peter; 2003. Economic and Financial Analysis of the China Renewable Energy Scale-Up Program (CREP): Volume I, The Economically Optimal Quantity of Grid Connected Renewable Energy, The World Bank.

Menanteau, Philippe; Finon Dominique; Lamy M.; 2003. Price versus Quantities: Choosing Policies for Promoting the Development of Renewable Energy, Energy Policy, Vol. 31, 799-812 Moner-Girona, M. 2009. "A new tailored scheme for the support of renewable energies in developing countries." Energy Policy 37: 2037-41.

Mitchell, C.; Bauknecht, D.; Connor, P.M.; 2006. Effectiveness Through Risk Reduction: A Comparison of the Renewable Obligation in England and Wales and the Feed-In System in Germany, Energy Policy, Vol. 34, 297305 O‟Brien, V., Sonntag- and E. Usher (2004), „Financing options for renewable energy‟, Environmental Finance, Renewables Finance special issue.

Palmer, Karen; Burtraw, Dallas; 2005.Cost-Effectiveness of Renewable Electricity Policies, Energy Economics, Vol. 27, 873-894.

REN21, 2010. Renewables 2010, Global Status http://www.ren21.net/globalstatusreport/REN21_GSR_2010_full.pdf Report, UNEP, SEFI and Bloomberg New Energy Finance 2010. Global Trends in Sustainable Energy Investment 2010, UNEP, Geneva, Switzerland.

Rickerson, W. and R.C. Grace 2007. "The Debate over Fixed Price Incentives for Renewable Electricity in Europe and the United States: Fallout and Future Directions." The Heinrich Boll Foundation.

24
that the unemployment rate is high in areas where the private economy is underdeveloped, whereas it is low in those areas with a flourishing private economy. 33

**Table 8.  Structure of Employment, by Type of Ownership in China (1980–2000, in Millions of Workers)**

||**Total**<br>**Emplo**<br>**yment**|**Urban**<br>**Employ**<br>**ment**|State-<br>owned<br>units <sup>a</sup>|Collective<br>units<br>a|Private<sup>b</sup>|Foreign|Self-<br>employed|**Rural**<br>**Emplo**<br>**yment**|TVE|Private|Self-<br>employed|
|---|---|---|---|---|---|---|---|---|---|---|---|
|**1980**|**423.6**|**105.3**|80.2|24.3|0.4|..|0.8|**318.4**|30.0|..|..|
|**1985**|**498.7**|**128.1**|89.9|33.2|0.5|..|4.5|**370.7**|69.8|..|..|
|**1990**|**693.1**|**170.4**|103.5|35.5|1.5|0.7|6.1|**471.1**|92.7|1.1|14.9|
|**1995**|**679.5**|**190.4**|112.6|31.5|8.6|5.1|15.6|**490.3**|128.6|4.7|30.5|
|**2000**|**720.9**|**231.5**|81.0|15.0|26.1|6.4|21.4|**489.3**|128.2|11.4|29.3|

Notes: a The “units” not only include state-owned or collective-owned enterprises, but also the state or collective-owned social services (public facilities, community and recreation services, etc.), education, public health, R&D institutions, and government/party agencies, etc.

b Under this heading are companies classified as private enterprises (normally informal), plus those classified as joint-owned units, limited shareholding corporations, limited liability corporations, and shareholding corporations. The last two categories actually appear only from 1998 on. Note that in China, an important amount of employees are not registered in any official category (floating employment). Source: _China Statistical Yearbook 2002_ , calculated from table 5-4.

Empirical studies also show that the private sector has achieved significantly greater productivity gains and R&D efficiencies and has contributed more to economic growth than all other sectors. 34 Wei, Zuobao, et al. studied the pre- and post-privatization financial and operating performance of 208 firms privatized during 1990-97. Results show significant improvements in real output, real assets, and sales efficiency, but no significant change in profitability. A further performance comparison between 41 fully state-owned firms and 41 privatized firms for the period of 1994-1999 shows that privatized firms experienced significant improvements in profitability, employment, and sales efficiency, especially those with over 50% voting control conveyed to private investors, while the SOEs experienced declines (see table 9). 35

> 33 Lee, Hong Yung, “Xiagang, The Chinese Style of Laying Off Workers”, _Asian Survey_ , V40, No. 6, November/December 2000.

> 34 Zhang, Anming, et al., “A Study of the R&D Efficiency and Productivity of Chinese Firms”, _Journal of Comparative Economics_ , V31, 2003, pp. 444-464; and Lo, V. and X. Tian, “Property Rights, Productivity Gains and Economic Growth: the Chinese Experience”, _Post-Communist Economies_ , V14, No. 2, 2002. 35 Wei, Zuobao, et al., “The Financial and Operating Performance of China’s Newly Privatized Firms”, _Financial Management_ , V32, No. 2, 2003.

15
classify these unknowns as low-skilled migrants<sup>12</sup> . Educational categories are built on the basis of country speci...c information and are compatible with human capital indicators available for all sending countries. A mapping between the country educational classi...cation is sometimes required to harmonize the data<sup>13</sup> .

# 3.2 Women’s share in OECD immigration

According to our estimates, the average share of women in the OECD immigrant population decreased from 51.6 to 50.6 percent between 1990 and 2000. Countryspeci...c shares range from 41.8 in Iceland to 59.8 in Poland . It amounts to 53 percent in the United Kingdom, 52.3 in Canada, 51 in the United States, 49.5 in France and 46.2 in Germany. This share increased or stagnated in almost all countries over the 1990s. The only signi...cant decreases are observed in Belgium (-3.8 percentage points) and Ireland (-2.8). Remarkable increases were observed in Austria (+11.3 percentage points), Portugal (+6.4) and, to a lower extent, in Turkey, Korea, Japan and Switzerland.

The average share of women in the OECD skilled immigrant population increased from 48.0 to 49.7 percent between 1990 and 2000. Country-speci...c shares range from 39.8 percent in Iceland to 56.4 in Poland. It amounts to 50.2 percent in the United Kingdom, 49.9 in the United States, 48.4 in Canada (the only country where there are more skilled women than skilled men), 46.6 in France and 45.2 in Germany. This share increased in almost all countries except in Belgium (-2.1) and Spain (- 1.4). Remarkable increases in female share were observed in the Czech Rep (+18.6 percentage points), Finland (+9.2) and Turkey (+9.1).

> 12Country speci...c data by occupation reveal that the occupational structure of those with unknown education is very similar to the structure of low-skilled workers (and strongly di¤erent from that of high-skilled workers). See Debuisson et al. (2004) on Belgium data.

13For example, Australian data mix information about the highest degree and the number of years of schooling.

11