rafmacalaba/datause-encoder-data huggingface dataset:
- 23 -

monitoring of the program after 1989 and the difficulties encountered earlier in the implementation were taclded to some extent. The internalization of the program in Burundi was manifested by the Govemment's active participation in the design of the latest phase of the reforms. This, in turn, made a difference in much steady and unfettered implementation of reforms in the post 1989 period, until the change of the Government. The example of Burundi illustrates that ownership is by no means a static concept and can be transformed over time and with effort from outright rejection and opposition to a fuller participation and active involvement of domestic constituencies.

Sandbrookl has offered an interpretation of the Ghanaian case, which validates the relevance of broadening the support base for reforms. He believes that rigorous programs of economic stabilizadon and adjustment in Ghana, that have been sustained for a decade, illustrate the evidence of "ownership". To own a recovery program, a government must have a hand in shaping the pace, sequence and mix of policies. In Ghana, a smal group of technocrats had made its voice heard by persuading the IMF and the World Bank to accommodate the Ghanaian Government's views on the pace and extent of devaluation, decontrol of prices, trade liberalization and privatization. While it is conceded that Ghana had a team of competen **t** echnocrats who steered the program well and won concessions from the IFI's and donors, the more demanding reforms such as privatization and public sector reforms have been stalled as other socio-econornic groups were not fully involved either in the design or at the implementation stage.

Senegal's example in the revision of the labor code provides an interesting illustration of the limitation of the consultation and participation process. In 1990, based on an in-depth study of the labor market in Senegal by the ILO, the Government decided that the labor code should be revised completely. To maximize support for adopting a new labor code, the Government involved the employers and trade unions in designing the new code and infonned and educated the public. But the revised code was not 18/ Sandbrook, R. "Political Liberaiiaion and the Politics of Economic Reform', USAID Conference Paper, Washington, D.C., 1993.
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# **References**

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- Acevedo, K. and Bornacelly, I. (2014). Panel Municipal del CEDE. _Documento Centro de Estudios sobre Desarrollo Económico_ , 2014-26.

- Acton, R. (2020). Effects of Reduced Community College Tuition on College Choices and Degree Completion. _Education Finance and Policy_ , pages 1–71.

- Barrera-Osorio, F. and Bayona-Rodríguez, H. (2019). Signaling or better human capital: Evidence from Colombia. _Economics of Education Review_ , 70:20–34.

- Bettinger, E. and Soliz, A. (2016). _Returns to Vocational Credentials: Evidence from Ohio’s Community and Technical Colleges. A CAPSEE Working Paper_ . Center for Analysis of Postsecondary Education and Employment.

- Blandhol, C., Bonney, J., Mogstad, M., and Torgovitsky, A. (2022). When is TSLS Actually LATE? Working Paper 29709, National Bureau of Economic Research. Series: Working Paper Series.

- Camacho, A., Messina, J., and Uribe Barrera, J. (2017). The Expansion of Higher Education in Colombia: Bad Students or Bad Programs? SSRN Scholarly Paper ID 2921965, Social Science Research Network, Rochester, NY.

- Card, D. (1995). Using geographic variation in college proximity to estimate the return to schooling, Aspects of labour market behaviour: essays in honour of John Vanderkamp. ed. _LN Christofides, EK Grant, and R. Swidinsky_ .

- Carranza, J. E. and Ferreyra, M. M. (2019). Increasing Higher Education Access: Supply, Sorting, and Outcomes in Colombia. _Journal of Human Capital_ , 13(1):95–136.

- Denning, J. T. (2017). College on the Cheap: Consequences of Community College Tuition Reductions. _American Economic Journal: Economic Policy_ , 9(2):155–188.

- Ferreyra, M. M., Avitabile, C., Botero Álvarez, J., Haimovich Paz, F., and Urzúa, S. (2017). _At a Crossroads : Higher Education in Latin America and the Caribbean_ . Directions in Development—Human Development. World Bank, Washington, DC.

- Ferreyra, M. M., Dinarte, L., Melguizo, T., and Sanchez Diaz, A. M. (2020). Estimating the Contribution of Short-Cycle Programs to Student Outcomes in Colombia.

21
13 by 4.9% (p<0.01). This impact is nearly identical for the pay for ability (6.5%; p<0.01). The coefficient estimate is largest for pay for performance contracts (6.8%; p<0.05). This is consistent with the fact that pay for performance contracts yield larger payoffs (pecuniary and non-pecuniary) for pro-social effort. Moreover, the difference in coefficients between the flat pay and pay for performance regressions is significant.

All pro-social pay systems do not, however, attract more able individuals. Under flat pay, _low_ ability individuals are significantly more likely to choose the pro-social task (p<0.01). A 1-slider decrease in the ability of the subject is associated with a 1.0% increase in the probability of choosing a pro-social contract. However, under both the pay for ability and pay for performance treatments, ability is not significantly related to task choice (p=0.66 and 0.25 respectively), and the two coefficients are not significantly different from each other.

This result is key: average ability in the mission sector, whether under the low-powered, pay for ability or high-powered pay for performance compensation systems, is no different than in the non-mission sector, even though pecuniary compensation in the non-mission sector is always higher. We verify this result by pooling the pay-for-ability and pay-for-performance treatments together and adding interaction terms that multiply a dummy for the pay system with ability and motivation variables (not shown). We find no significant differences by treatment. Motivated subjects are equally likely to join the mission sector under pay-for-ability and pay-forperformance (p=0.79). Similarly, high ability subjects are equally likely to join the mission sector under either pay scheme (p=0.86). Thus, both pay schemes attract a similar profile of workers, though high ability workers are more likely to join either pay scheme relative to flat pay.

**Table 2:  Who chooses the mission sector under different pay schemes?**

|Dependent Variable: Secto<br>Treatment|r Choice (1 = Joi<br>Flat<br>I|n Mission Sec<br>Pay-for-<br>Ability<br>II|tor)<br>Pay-for-<br>Performance<br>III|
|---|---|---|---|
|Amount Sent in Dictator Game|0.987***<br>(0.35)|1.315***<br>(0.31)|1.498**<br>(0.59)|
|Ability|-0.039***|0.011|0.006|
|(Effort Exerted in Piece Rate)|(0.01)|(0.01)|(0.02)|
|Constant|2.624**|-1.770*|-0.964|
||(1.13)|(0.95)|1.70|
|Log Likelihood|-111.3|-123.7|-35.3|
|Pseudo R-squared|0.0854|0.0799|0.105|
|P-value|0.000|0.000|0.016|
|Observations|176|195|60|

Note: * p<0.1, ** p<0.05, *** p<0.01. Logit specification, standard errors in parentheses. The dictator game variable is divided by 1000 for presentational convenience. Please see table A1 for the same table but with a full set of controls.
# **Table 1: Price Shocks and Billionaire Net Worth**

|**Model**|**Country and Year**<br>**Fixed Effects**|**Billionaire and Year**<br>**Fixed Effects**|**Billionaire and Year**<br>**Fixed Effects**|
|---|---|---|---|
|**Dependent Variable**|**Log of**|**Billionaire Net Worth (in B**|**illions)**|
||**(1)**|**(2)**|**(3)**|
|Log difference of commodity Net Export Price Index<br>(historic rolling weights)|0.622***|0.387***|0.380***|
||(0.187)|(0.148)|(0.146)|
|Log of GDP (constant 2010 US$)|||0.145***<br>(0.053)|
|Constant|0.888***|0.467***|-3.673**|
||(0.030)|(0.030)|(1.526)|
|Country Fixed Effects|YES|NO|NO|
|Billionaire Fixed effects|NO|YES|YES|
|Year Fixed Effects|YES|YES|YES|
|Number of observations|20,512|20,512|20,502|
|R2|0.064|0.285|0.289|
|Adjusted R2|0.060|0.284|0.289|

note: *** p<0.01, ** p<0.05, * p<0.1, Robust Standard Errors Clustered at the Billionaire level

**<u>Table 2: Natural Resource Rents and Billionaire Net Worth</u>**

|**Model**|**Country and Year**<br>**Fixed Effects**|<br>**Billionaire and Year**<br>**Fixed Effects**|**Billionaire and Year Fixed**<br>**Effects**|
|---|---|---|---|
|**Dependent Variable**||**Log of Billionaire Net Worth**|**(in Billions)**|
||**(1)**|**(2)**|**(3)**|
|Total natural resources rents (% of GDP)|0.012***|0.014***|0.013***|
||(0.004)|(0.003)|(0.003)|
|Log of GDP (constant 2010 US$)|||0.087**<br>(0.038)|
|Constant|0.670***|0.451***|-2.037*|
||(0.082)|(0.030)|(1.091)|
|Country Fixed Effects|YES|NO|NO|
|Billionaire Fixed effects|NO|YES|YES|
|Year Fixed Effects|YES|YES|YES|
|Number of observations|18,382|18,382|18,375|
|R2|0.066|0.276|0.277|
|Adjusted R2|0.062|0.275|0.277|

note: *** p<0.01, ** p<0.05, * p<0.1, Robust Standard Errors Clustered at the Billionaire level 14
64

**Figure 11: Demographic Effects**

<!-- Start of picture text --> 0.4 - - -<br>01 ---------- ----- ------ ------- ------ --------- --<br>0.0<br>= - 0 .2 - ----- .4 --- ---- -------- - --<br>0<br>n) O .6 4 0 -- ---. -- --- ---- .~~~~~~~~~~~~~~~~~~~~~~------- - -------- ------<br>-1.2 _ __ _ - __ - - - - - - - - - _ _ _ __ _<br>c > °o Q,b ,0 + > , O , OK V<br>Percentiles<br>-mu (d) ~mu(d), aiphas, betas, gammas<br><!-- End of picture text --> Source: "Pesquisa Nacional por Amostra de Domicilios" (PNAD), 1976 and 1996.
to invest in the future as compared with that of investing today; (dW/do<sup>2</sup> > 0).' If uncertainty is higher, the value of waiting to receive more infornation is indeed higher and the required flexibility premium should be higher too. In the numerical application, we will see that the investment decision is very sensitive to the estimate or perception of the underlying uncertainty. One caveat is in order at this point. The uncerainty is assumed to be exogenous, but it can be influenced by the damages from global warming and the degree of policy intervention --uncertainty may increase (or alternatively decrease) with the level of cumulative emission from the use of fossil fuel., As discussed in the introduction, not only is the optimal investment timing influenced by the possibility of waiting for better information, but also by the evolution of irreversible damages during the waiting period. Two basic assumptions can be tested in the model. First, it can be assumed that irreversible damages would remain constant, whatever is the starting date of intervention. The advantage is that the expected time when the investment will take place can be directly deduced from the option-pricing approach:' Second, it is certainly more realistic to assume that the level of irreversible damages is correlated positively with the length of the waiting period. Postponing the intervention will therefore translate into a higher level of CO2 emission which, in turn, 4. Note that this is not always true for the individual standards deviations, since the total effective standard deviation is a quadratic function of the two standard deviations and the correlation, see the Appendix.

5. On this issue, see the recent paper by Chichilnisky and Heal (1993).

6. For a prof see World Bank (1991).

6
22 distribution. While women were at the 40th percentile in the observed earnings distribution, they were only at the 30th to 33rd percentile of the residual earnings distribution.2' In western economies, male advantages in work experience, job tenure, and proportion with college training serve to explain some of the pay difference between men and women. In Slovenia, the opposite holds. Women do worse in the residual distribution than in the observed distribution. The main reason appears to be that women had superior education. Women were less likely than men to have less than an elementary education or a vocational degree, the two educational categories that performed worst throughout the transition. On the other hand women were more likely to hold middle school or university degrees, the educational categories that did best in the transition.

Nevertheless, both the observed and the residual wage data indicate that women rose from four to five percentage points in the male wage distribution over the five year period spanning the Slovenian transition. In contrast, Blau and Kahn(1994) reported a 5.5 percentage point gain for U.S. women ovar a twelve year period from 1975 through 1987.

At the bottom of Table _5,_ the changes in male-female wage differentials are decomposed into the four components. Negative numbers indicate factors that are increasing women's pay relative to men's pay. Over the five year period, the first three terms serve to reduce wage differentials between men and women, while the fourth term which captures the effect of increasing inequality in the residual wage distribution raises the gender wage gap. Almost all of the changes in the wage gap occur after 1989. Although there were nontrivial values for the last three terms in the 1987-1989 period, they canceled each other out. For the full period, the greatest impact occurred through the gap effect with women gaining by moving up the male residual earnings distrbution. The next largest effect was from increasing inequality in the residual wage distribution. Because women were 21B1au and Kahn's estmates for the sample of westem economies show female percentile sus in male residual earnings distributions varying from .16 in West Germany to .31 in Austria.
the size of the implicit output subsidy under the DEPS. The net impact depends on which effect predominates.

We found that changing this parameter does not significantly affect the importance of overlapping policies. Overlapping policies such as RPS and IEP improve the cost-effectiveness of DEPS by enabling more renewable electricity production and increasing cost pass-through. Changing capital transformation elasticity within a sector does not significantly impact these channels, because the supply elasticity of renewables is also affected by their own subsectorspecific resource input. This resource input accounts for the special integration costs associated with renewables and is a fixed factor, limiting the extent of renewables’ output change due to capital transformation elasticity. Also, capital transformation elasticity within a sector affects the supply elasticity of output from a subsector but does not directly affect the elasticity of the total output from that sector. Consequently, the response of results to overlapping policies does not vary significantly with changes in capital transformation elasticity.

**Table D2. Sensitivity Analysis with Different Settings of Capital Transformation Elasticities**

||**Emissions**<br>|**Costper**|**Ton Abateme**|**nt(yuan/t)**|**Cost**<br>|**Ratio**<br>|
|---|---|---|---|---|---|---|
||**Reduction**||||**DEPS-R2/**|**DEPS-NO/**|
||<br>**(%)**|**CAT-NO**|**DEPS-R2**|**DEPS-NO**|<br>**CAT-NO**|<br>**CAT-NO**|
|**Halved**|||||||
|Phase 1|-2.7|6.3|17.2|22.4|2.7|3.6|
|Phase 2|-5.8|10.2|20.1|23.7|2.0|2.3|
|Phase 3|-11.8|16.9|24.5|36.6|1.4|2.2|
|All|-9.3|15.7|23.7|34.6|1.5|2.2|
|**Central**|||||||
|Phase 1|-2.6|5.4|15.3|19.6|2.8|3.6|
|Phase 2|-5.5|8.8|17.3|21.0|2.0|2.4|
|Phase 3|-11.0|14.1|22.5|32.0|1.6|2.3|
|All|-8.7|13.1|21.5|30.2|1.6|2.3|
|**Doubled**|||||||
|Phase 1|-2.5|4.7|14.1|17.2|3.0|3.7|
|Phase 2|-5.4|8.8|15.7|18.8|1.8|2.1|
|Phase 3|-10.7|14.1|21.1|28.9|1.5|2.1|
|All|-8.4|13.1|20.1|27.2|1.5|2.1|

Table D3 presents the results with varying settings for electricity-non-electricity substitution elasticity. In our central parameter setting, this elasticity is calibrated based on data for the price elasticity of demand for electricity, which is -0.5 following Hu et al. (2019). To account for uncertainties, we consider two alternative cases: (1) Setting the electricity-non64
Assaad, R., Krafft, C., & Sieverding, M. (2021a). _Survey of Young People in Jordan—UNICEF ACSS Dataverse V1.0_ (V1.0) [dataset]. ACSS Dataverse.

Assaad, R., Krafft, C., & Sieverding, M. (2021b). _Youth Transitions to Adulthood in Jordan: High Aspirations, Challenging Realities_ (Issue November).

Assaad, R., Krafft, C., & Yassin, S. (2018). Comparing retrospective and panel data collection methods to assess labor market dynamics. _IZA Journal of Development & Migration_ . https://doi.org/10.1186/s40176-018-0125-7 Assaad, R., & Salemi, C. (2019). The Structure of Employment and Job Creation in Jordan: 2010-2016. In C. Krafft & R. Assaad (Eds.), _The Jordanian Labor Market Between Fragility and Resilience_ . Oxford University Press.

Bartik, A. W., Bertrand, M., Lin, F., Rothstein, J., & Unrath, M. (2020). Measuring the labor market at the onset of the COVID-19 Crisis. _Brookings Papers on Economic Activity_ , _Special Edition_ , 239–268. https://doi.org/10.1353/eca.2020.0010 Beaujouan, J., & Rasheed, A. (2020). The Syrian Refugee Policy of the Jordanian Government.

In _Syrian Crisis, Syrian Refugees_ (pp. 47–63). https://doi.org/10.1007/978-3-030-35016-1 Betts, A., Bloom, L., Kaplan, J. D., & Omata, N. (2017a). _Refugee economies: Forced_ _displacement and development_ (First edition). Oxford University Press.

Betts, A., Bloom, L., Kaplan, J., & Omata, N. (2017b). _Refugee Economies: Forced_ _Displacement and Development_ (First edit). Oxford University Press.

Borjas, G. J., & Cassidy, H. (2020). The Adverse Effect of the COVID-19 Labor Market Shock on Immigrant Employment. _National Bureau of Economic Research_ , _27243_ .

Cortes, G. M., & Forsythe, E. (2020). The Heterogeneous Labor Market Impacts of the Covid-19 Pandemic. _SSRN Electronic Journal_ . https://doi.org/10.2139/ssrn.3634715 30
# The PEG Trial Plots

The PEG trial were started in response to the crop attack by Heliothis in 1987/88. Several different plots, each measuring half an acre were demarcated, side-by-side, at Palladigunta, in the heart of the Guntur cotton belt. Different cultivation practices were implemented on each plot such that some predetermined hypotheses could be best addressed. The basic objective of the trials is to demonstrate to the farmer how heliothis can be controlled effectively through the proper use of pesticides in general and SPs in particular. In fact, the trials are also aimed at demonstrating that better management practices in cotton cultivation can substantially reduce pesticide use and increase cotton yields. Thus, the PEG plots have incorporated many of the important elements of an IPM techniques package. The specific practices adopted were: a) Agronomic practices as recommended by the Andhra Pradesh Agricultural University (APAU), in respect of pre(field) preparation, fertilizer usage, weeding, etc., relevant for the cotton varieties being cultivated. These "optimal" practices were implemented both on the trial plots as well as the fields under traditional farmer practices (the control plots, to be used for comparison purposes).

b) Regular scouting from 40 days after sowing, at 3-5 day intervals, to estimate plant damage, larvae count, egg count, etc. c) Spraying in accordance with predetermined Economic Threshold Levels (ETLs), i.e., need based use of the pesticide instead of a 66
U.S. entry rates (EntryUS) for broad groupings of NACE codes.<sup>26</sup> Annex 3 shows U.S. entry rates for all 2-digit NACE codes. In comparing the Dun and Bradstreet data to our 1-year European entry rates, we find in the U.S. similar high entry rates in the computer and communications industries and low entry rates in industries such as mining, and water utilities. In general, we see higher entry rates in high-tech sector and lower entry rates in infrastructure related sectors.

In Table 5, we examine the size (measured by number of employees) distribution of entering firms, averaged over 1998 and 1999. The data confirm that most of the entry occurs in small firms. Interestingly, we find a greater fraction of new, larger firms in the Eastern European transition countries. This suggests that new, private firms are emerging across all size groups, rather than only small firms that require time to grow. This may also reflect a number of larger, state-owned firms that continue to be privatized and reincorporated following the transition.<sup>27</sup> On average, we find that about 63% of new firms have less than 10 employees, 23% have 10-50 employees, 12% have 50-250 employees and 2% have more than 250 employees. Since new firms in this largest category are likely to be existing firms that reincorporate following a merger or acquisition, we check that our qualitative results hold when we exclude new firms with more than 250 employees.

# **II. Methodology**

We explore the differential effects of certain country characteristics on entry across industries with different natural demands for that characteristic. In other words, we are interested in the interaction between country and industry-specific variables. We use industry indicators to control for level differences across industries and country indicators to control for level differences across countries. The model is as follows:

> 26 We use the International Concordance between the U.S. 1987 SIC and the NACE Rev. 1 industrial classifications to match the 4-digit level SIC codes used by D&B with the 2-digit level NACE codes used in Amadeus.

> 27 An exception to the transition countries is Romania, which includes over 200,000 firms with less than 10 employees.

15