rafmacalaba/datause-encoder-data huggingface dataset:
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fiscal reforms (Chan 1997).<sup>4</sup> Much of the emphasis that cities place on land leasing in China’s competitive federalism framework stems from the fact that fiscal rules allow them to keep the land-leasing revenues that they mobilize and grant municipalities a great deal of freedom to act as entrepreneurs in the local land market.

The purchaser of a land lease acquires land rights for a period of 40 to 70 years, depending upon the type of property development. Land that is ‘sold’ and approved for development can be reclaimed by government if not developed within a specified time period. Originally, municipalities transferred land rights to developers primarily by private negotiation. In the mid-1990s, a review by the Ministry of Land and Resources found that more than 95 percent of all transfers had taken this form. (Sun, 1995) Private negotiations with developers, however, provided a fertile ground for corruption, with consequent revenue loss to government. In 2002 central authorities promulgated a new circular instructing municipalities to conduct all land leasing through public bidding at auction. Municipalities were slow to accept the new limitations (Beijing issued its order to conduct all municipal land transfers through public competition only in 2004). However, according to central statistics, the percentage of municipal land transfers occurring through auction or public bidding rose from 15 percent in 2002 to 33 percent in 2003 (China Daily, 2004b), and has continued to rise, becoming the primary form of conveyance in economically advanced cities.

# **Revenue Generated from Land Sales**

Because comprehensive municipal budgets are not released to the public, it is difficult to put together reliable data on the magnitude of land leasing except through case studies. Table 1 summarizes information from several different case studies regarding land-leasing revenues and their size relative to total local spending or the local capital budget. Although land leasing is viewed as an infrastructure-financing tool by Chinese municipalities, there is no legal requirement to dedicate revenues to the capital budget.

> 4 The decision to assign all revenue from land leasing to municipalities in part recognized on-theground reality.  The State Auditing Authority found that in 1991 and 1992, 80% of the land leasing revenues generated by sample municipalities were concealed from the local fiscal authority, and of the amount received by the fiscal authority 90% was assigned to the local discretionary budget rather than shared with central government according to the rules then in effect.

5
removal for villages along the planned right-of-way. We estimate the potential employment and income gains from the country-level upgrading and maintenance cost estimates in Appendix Tables A4 and A5. Drawing on results from a recent UNDP study of labor-intensive road construction in Mozambique (UNDP, 2002), we assume a 35% labor share of total construction expenditure. Dividing the resulting wage bill by the annual wage per road worker, we arrive at estimated annual employment per country for initial upgrading and subsequent maintenance.<sup>40</sup> To put the results in perspective, we also calculate populations for areas contiguous to the network in each country.<sup>41</sup> We present the employment and population results for all network countries in Appendix Table A6.

Our results indicate a variety of employment and income impacts, from modest to extremely large. Democratic Republic of Congo provides an illustration of large-scale benefit generation, with total network length of 12,184 km, between 2,000 and 4,900 abutting settlements, and abutting population (within 5 km of the road) between 1 and 7.3 million. At estimated Congolese wages ($500/year), network upgrading generates 40 We conservatively estimate the annual wage for rural road workers as 75% of per capita income. This is probably too high, so our estimated range of employment benefits is probably conservative. 41 First, we estimate the number of settlements abutting the network in each country. Using a Geographic Information System (GIS) and available spatial data, we develop relatively precise estimates of villages within 5 km of network roads in Mozambique, Mali and Burkina Faso. We divide total network distance in each country by the estimated number of settlements to obtain the estimated road interval separating settlements. The estimated intervals for the three countries are 2.70 km (Burkina Faso), 4.06 km (Mozambique) and 5.04 km (Mali). From these results, we set low- and high-range interval estimates for Africa at 2.5 and 6.0 km. Then we multiply by network length in each country to obtain low and high numbers for settlements abutting network roads. Using the three-country spatial dataset, we also estimate the average populations per settlement in the network’s 5-km buffer areas: 1,274 (Burkina Faso), 1,394 (Mozambique) and 700 (Mali). These averages are somewhat higher than for villages further than 5 km from a main road. For our extrapolation to other countries, we set the low- and high-range estimates at 500 and 1,500 people per settlement. We (very) conservatively bound our population estimates as follows: For each country, we obtain the lower-bound network-abutting population estimate by multiplying the lowerbound estimate of network-abutting settlements by the lower-bound estimate of population per village. We obtain the upper-bound population estimate by multiplying the upper-bound estimate of settlements by the upper-bound estimate of population per village.

40
# _The Incorporation of Chinese Domestic Stocks into the MSCI Emerging Markets Index_

In June 2013, MSCI released the first official document discussing the potential inclusion of A shares in the MSCI Emerging Markets Index.<sup>10</sup> Until then, the only Chinese stocks tracked by MSCI were those of foreign listed firms.

Following several consultations between 2014 and 2017, MSCI announced in June 2017 the inclusion of A shares in the MSCI Emerging Markets Index (Appendix Table 3). Only A shares eligible through the Stock Connect program were added to the MSCI Emerging Markets Index. Large capitalization (Large Cap) shares were included with an inclusion factor of 5 percent in 2018.<sup>11</sup> The inclusion factor subsequently increased to 10 percent in May 2019, 15 percent in August 2019, and 20 percent in November 2019.<sup>12</sup> The addition of Mid Cap A shares was announced in 2017 and implemented in 2019.

# _Aggregate Trends_

The internationalization of equity markets in China coincided with rapid growth in equity market capitalization. The market capitalization of domestic listed firms grew especially fast during the implementation of the Stock Connect program (2014-2016) and the MSCI incorporation (201820). The Chinese equity market capitalization grew faster than GDP and the capitalization in Hong

> 10 This also implied adding the A shares to all the related MSCI indexes. MSCI indexes are the most widely followed equity market benchmarks by institutional investors worldwide (Hau, 2011; Cremers et al., 2016).

> 11 ‐ The inclusion factor is the proportion of a security’s free float adjusted market capitalization that is allocated to the index.

> 12 Other foreign equity benchmark indexes followed MSCI. In September 2018, the Financial Times Stock Exchange (FTSE) Russell announced the official inclusion of China’s A shares into its Global Equity Index Series (FTSE GEIS). In September 2019, A shares were officially included in the FTSE indexes with an inclusion factor of 5 percent. In August 2019, FTSE Russell increased the inclusion factor of A shares from 5 to 15 percent. In September 2019, Standard and Poor’s (S&P) Dow Jones Indices added China’s A shares to its S&P Global Broad Market Index (BMI) at an inclusion factor of 25 percent.

8
(Angeletos and Dellas, 2020).

Identifications of technology shocks using the long-run identification of Gal ́ı (1999) have been found to be subject to substantial bias where non-technology shocks account for a non-trivial proportion of output fluctuations (Chari et al., 2008). In contrast, the spectral identification method tends to be more robust than other SVAR identifications of technology shocks in the presence of large confounding business-cycle shocks to productivity growth (Dieppe et al., 2019, 2021). The spectral SVAR identification is applied to a VAR containing the log of labor productivity, log employment per capita, consumption as a share of GDP, investment as a share of GDP, consumer price inflation, and monetary policy rates (when available). For illustrative purposes, TFP is also included in the VAR to observe differences relative to the response of labor productivity to the technology shock.

A Fourier transform is used to estimate the contributions of potential structural shocks at various frequencies. Effectively this involves the application of a band-pass filter (Christiano et al., 2003) using the reduced-form coefficients of a VAR, identifying the spectral density of the variables within a particular frequency band. The technology shock is then identified as the shock that explains the largest share of the variance of labor productivity at the desired ( _long-horizon_ ) frequency.

Identifying technology shocks through restrictions that explain the majority of low (long-term) frequency volatility of productivity is a novel approach. This methodology has previously been used to assess the types of shocks that drive the business cycle. For example, Angeletos and Dellas (2020) find that a single shock drives the majority of the variance of a range of macroeconomic variables at business cycle frequencies, and DiCecio and Owyang (2010) use a similar methodology to identify technology shocks.

A VAR representation of the spectral density of Y is generated using the Wold representation of the VAR (assuming it is invertible): where _B_ are the reduced-form VAR coefficients and (assuming invertibility) D represents the MA coefficients on the reduced form innovations _u_ at each horizon. By post-multiplying _Yt_ by _Yt−τ_ , a series of autocorrelations are generated, which in turn can generate the spectral density of the endogenous variables at frequency _ω_ , based on the reduced-form MA coefficients _D_ � _e_<sup>_−iτω_�</sup> = � _I −_ � _B_ 1 _Le_<sup>_−iω_</sup> + _B_ 2 _L_<sup>2</sup> _e_<sup>_−i_2</sup><sup>_ω_</sup> + _. . . BpL_<sup>_p_</sup> _e_<sup>_−ipω_��</sup><sup>_−_1</sup> : To assess the spectral density within a frequency band, _SY Y_ ( _ω_ ) is integrated over the band of interest _ω_ = [ _<u>ω</u> , ω_ ̄] To identify technology, the band is restricted to frequencies that are longer than 10 years in order to exclude business cycle frequencies. The shock that maximizes the variance of labor productivity over the desired frequency is the eigenvector associated with the largest eigenvalue 7
**Table 1: Requirements for and responses of** **_Chile Solidario_ (CHS)**

|**Requirements for CHS**|**Responses of CHS**|
|---|---|
|**Implement a model to actively find and enroll**<br>**families who were not accessing programs and**<br>**social services.**|Intensively use the information available in the<br>targeting instrument not only to qualify eligibility, but<br>to identify potential beneficiary families.|
|**Involve beneficiaries in the social intervention**<br>**process, promoting a shared responsibility**<br>**approach in the task of improving their living**<br>**conditions.**|The intervention used a “Task Centered Approach”,<br>based on results.<br>A mechanism was established through signing of a<br>formal participation agreement (called contract)<br>between each beneficiary family and CHS, where<br>family achievements were agreed upon.|
|**Having a Development Agent to support families**<br>**in the knowledge and use of institutional and**<br>**social networks.**|A personalized psychosocial support service was<br>developed, provided by a social worker, called<br>Family Support service.|
|**Rearrange available resources to improve the**<br>**focus on extremely poor families.**|A coordination system of social services and<br>benefits was established in order to ensure that<br>various benefits were supplied to the same<br>beneficiaries.|
|**Define common and measurable objectives for**<br>**both the institutions and the beneficiaries.**|The social intervention was structured around 53<br>minimum quality of life conditions, organized in 7<br>dimensions: identification, health, education, family<br>dynamics, housing, work and income (see Table 4).|
|**Families need a temporary cash transfer to**<br>**support financing costs associated to accessing**<br>**social services.**|A monthly transfer, for 24 months, was included in<br>the design, with the amount decreasing every 6<br>months. The purpose of the transfer was to finance<br>transaction costs related to the process of social<br>inclusion.|
|**Ensure economic resources to**<br>**families to**<br>**support those who are not able to generate their**<br>**own income.**|Transform existing cash subsidies into targeted and<br>guaranteed cash transfers to support vulnerable<br>family members and facilitate their participation in<br>the network of social services.|
|**Increase available opportunities in the local**<br>**network of services.**|The design included a Local Intervention Network,<br>coordinated by the Municipality.|
|**Having appropriate and sufficient information to**<br>**arrange an effective service delivery process.**|Installation of a Comprehensive Social Information<br>System to register, monitor and supervise the<br>implementation of CHS in order to follow-up demand|

11
33 Scenario 16. **Staring the funded tier with the generation younger than 30 In 1997, lowering social security tax for all worker by 1%** a year from 1997 to 2004 (to 25% in 2004) **with** contribution to the funded tier remaining at 10% for **the** whole period, Increasing retirement ages to **65,** and maintaining constant replacement ratio under PAYG

||1995|1996|1997|1998|2000|2005|2010|2020|<br>2030|
|---|---|---|---|---|---|---|---|---|---|
|As % of formal GDP||||||||||
|Payroll contributions (all)|8.43|9.14|9.14|9.43|9.35|9.12|9.44|9.99|<br>10.22|
|Total PAYG expenditure|8.49|9.64|9.99|10.23|10.33|8.30|8.30|9.01|<br>8.99|
|Balance|-0.06|-0.50|-0.85|-0.80|-0.97|0.81|1.15|0.98|<br>1.23|
|Funded Tier (trillions of Kbv., curr. price)||||||||||
|Total assets (stock)|||61|159|502|2725|8674|53770|235106|
|Gov't borrowing from Funded tier|||61|87|162|222|477|2935|9121|
|(as % of formal GDP)|||0.6%|0.7%|0.9%|0.7%|1.0%|2.2%|<br>2.7%|
|Stock of govt debt|||61|159|502|1957|4980|32068|153224|
|(as % offormal GDP)|||1%|1%|3%|6%|10%|24%|45%|
|Extra resources needed for PAYG|||-86|-97|-166|0|0|0|0|
|(as % of formal GDP)|||-0.8%|-0.8%|-1.0%|0.0%|0.0%|0.0%|<br>0.0%|
|Average replacement ratio|29%|29%|30%|31%|31%|31%|31%|31%|31%|
|System dependency ratio|111%|118%|114%|107%|99%|71%|68%|71%|69%|
|Share of formal sector employment|59%|59%|62%|65%|69%|71%|71%|72%|72%|

These scenarios clearly differ in terms of distributional impact. One can distinguish three relevant population groups: those already retired; those still in the labor force who will be covered under the new plan; and those also in the labor force but younger who will be covered partially or fully under the new plan. The first scenario (10) gives all the benefits of the reform to the generations enrolling under the new plan. They will benefit from higher pensions and higher growth; some of them as well as the next generations will have to pay back the accumulated debt. The other population groups can only benefit from the slightly higher growth that the reform would bring about. The second and third scenarios (1 1 & 12) shift additional benefits of the reforms to those still in the labor force who will not participate in the new plan. As a result, the burden passed on future generations increases. The fourth scenario (13) lowers the burden passed on future generations by imposing higher costs to those currently retired.

It would be preferable for equity reasons that each of these population groups gain from the reform. This would also increase social support. In addition it would be highly inequitable to make the poorest population groups who have borne all the costs of the transition to a market economy bear additional costs linked to the implementation of a pension reform. For all these reasons scenarios 1 1 and 12 appear as the best options. They at least maintain a constant replacement ratio to those already retired and provide some benefits to those still in the labor force who will nevertheless retire under the old scheme. The election between them amounts to
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<mark>for households and their lack of granularity in assessing the ways in which they are poor.</mark><sup>9</sup> <mark>Unfortunately, we are again limited by the availability and informational content of the existing data with respect to the outcomes we would like to measure, as the best known multidimensional poverty indicators are available only since 2010.</mark><sup>10</sup> <mark>We thus perform this part of the analysis using indicators that proxy some of the components in multi-dimensional poverty indicators, for which longer time series exist.</mark> <mark>Indicators proxying access to nutrition and electricity, as well as health outcomes also suggest that defaults lead to marked declines in standards of living. All of our outcome variables are indexed to 100 the year before default. Calorie availability consistently lags in defaulting countries with the cumulative gap relative to synthetic controls growing to 4 percentage points ten years after default. Our findings on energy supply, though not statistically significant, also suggest that defaulters lag their controls by about 10 percentage points cumulatively after four years. Infant mortality and life expectancy show significant cumulative gaps for defaulters relative to their controls. On average, by year ten, defaulters have 13% more infant deaths than the counterfactual. This result is consistent with Baird et al. (2011) who find that infant mortality is sensitive to aggregate income shocks. And those infants that survive are expected to have shorter lives: with the life expectancy dropping to 1.5 percent below the synthetic counterfactual – the equivalent of 1.2 years – below that in the synthetic control. This result is consistent with Baird et al. (2011) who find that infant mortality is sensitive to aggregate income shocks.</mark> <mark>The last set of findings presented here take a more detailed view of how poverty and the incomes of the poor are affected by defaults – albeit with a reduced sample that should be interpreted as a broad case study. Based on the 11 cases for which we have sufficient surveysourced data, we find that there is considerable heterogeneity in “excess poverty” outcomes. In four cases there are sizable increases in poverty over what would be implied by the growth shock. Another four cases remain close to zero excess poverty and two show negative excess poverty. As for incomes, we identify peak-to-trough windows in per capita GDP levels and look at the cumulative change in income going to different segments of the population. We find that the bottom 10 percent’s income level dropped on average by a cumulative 9 percent while the</mark>

> 9 <mark>It is worth noting that this literature is extensive and though there is agreement that poverty headcounts may be insufficient, there is ample debate about the right methodology to construct a multi-dimensional poverty index (Alkire 2015) or multiple indices (Ravallion 2011).</mark>

> 10 <mark>See OPHI GMPI.</mark>

6
not based on fleet average, every single vehicle model sold in China is required to conform to the standard for its weight class in terms of maximum liters consumed per 100-km (Pew, 2004). A recent study by the China Automotive Technology and Research Center finds that the standards implemented in 2005 improved overall passenger vehicle fuel efficiency from 26 mpg in 2002 to 28.4 mpg in 2006, or by about 9 percent, in spite of increases in gross weight and engine displacement (ICCT, 2007).

South Korea announced, in 2004, that it will implement mandatory fuel economy regulations – the Average Fuel Economy (AFE) standard – to replace the existing system of voluntary standards in 2006 for domestic cars and in 2009 for imports. The standards are set at 34.4 CAFE-normalized<sup>15</sup> mpg for vehicles with engine displacement less than 1,500 cubic centimeters (cc) and 26.6 mpg for those over 1,500 cc (ICCT, 2007). However, despite being mandatory, there are no fiscal or criminal penalties for violating the AFE standard, with only a public shaming to serve as deterrent (Pew, 2004). The new AFE standard is partly a reaction to declining average fuel economy resulting largely from the growing popularity of SUVs, but since fuel economy standards remain static from 2006 onwards while the market share of larger, more powerful vehicles continues to rise gradually, South Korea is the only country with mandatory fuel economy standards where fleet average fuel economy is expected to deteriorate through 2012 (ICCT, 2007).

In India, the “Mashelkar Committee” proposed voluntary fuel economy standards for the automotive industry in 2002 (Mashelkar, 2002). Manufacturers, however, failed to commit to the voluntary scheme within the four year grace period granted by the

> 15 U.S. Corporate Average Fuel Economy (CAFE) test method. Other methods include New European Drive Cycle (NEDC), and Japan 10-15 Cycle.

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