rafmacalaba/datause-encoder-data huggingface dataset:
# **Figure 4 Labor moving to lowerproductivity services**

# **Figure 5 Relative labor productivity**

(ratio of sectoral to aggregate labor productivity) (share of total employment) <!-- Start of picture text --> Trade, restaurant, hotel<br>Non-market services<br>Finance, real estate, business services<br>0.25<br>0.20<br>0.15<br>0.10<br>0.05<br>0.00<br>1978 1983 1988 1993 1998 2003 2008<br><!-- End of picture text --> Source: GGDC 10-Sector Database, Timmer et al. (2015); authors’ calculations.

<!-- Start of picture text --> Trade, restaurant, hotel<br>Non-market services<br>Financial, real estate, business services<br>10<br>8<br>6<br>4<br>2<br>0<br>1978 1983 1988 1993 1998 2003 2008<br><!-- End of picture text --> Source: OECD; authors’ calculations. Note: A higher STRI indicates a more restrictive regime.

In the decade after the global financial crisis, aggregate labor productivity growth in China weakened to 7.4 percent per year, from 9.0 percent in 1999-2008. A slowdown was observed across sectors but services experienced the largest decrease from an annual average of 8.1 percent in 1999–2008 to 4.6 percent in the most recent decade. Lower aggregate productivity growth has been partly due to China’s economic rebalancing away from foreign demand and industry toward higher domestic consumption and services. Today resources are being reallocated from agriculture and, since 2013 and at a much slower pace, from industry into services.

Following Baumol (1967), the decline in productivity growth as the economy matures is almost inevitable but, in China’s case, there is scope to improve labor productivity in services. As incomes rise, households spend more of their income on services. Correspondingly, higher income countries tend to have a higher share of employment in services, where productivity is generally lower than in industry. However, China could implement policies that boost service sector productivity. One area, for example, is market competition, as services in China have been much less open to competition and FDI than industry. By one measure—the OECD services trade restrictiveness index (STRI)—China, along with the Russian Federation, Indonesia, and India, ranks considerably below the OECD countries and has shown limited improvement over time (Figure 6).

6
supplier is also serving ...rm k; i.e. s 2 Skt; or In other words, Sikt<sup>sisasupplierspeci...csiblingdummythatindicateswhethersuppliersisa</sup> common supplier of i and k in year t: Alternatively, let NSikt be the total number of common suppliers between i and k in t; Then ...rms i and k are siblings in t if NSikt � 1: Note that sibling ...rms, in the context of this paper, have nothing to do with their ownership structure, and certainly do not imply that they share same parent ...rms or are part of the same conglomerate group. Moreover, even though I only have information on the set of local suppliers for each ...rm in 2003, there are two local suppliers that are only set up in the latter part of the sample period. For ...rms that use these newer suppliers, their sets of local suppliers exhibit year to year variations. This is why Sit and Sikt<sup>sareindexedby</sup> t: Foreign Sibling P resence or FDI Sibling Presence (FSPit) of ...rm i in year t; is constructed by summing the Foreign Presence of all its siblings from all its local suppliers, It is also equivalent to averaging the foreign ownership share of i<sup>0</sup> s siblings in j, weighted by each sibling’s capital share in the industry and the number of common input suppliers with the sibling in year t. Comparing (4) with (7) it is easy to see that FSPit is very similar to IFPjt; except that it only focuses on the foreign presence of the sibling ...rms rather than all ...rms in the industry. If a domestic ...rm i does not share any local input suppliers with FDI ...rms, (i.e. NSiktFSk = 0; 8k); 10
Policy Research Working Paper 8374

# **Abstract**

Crop yields in smallholder systems are traditionally assessed using farmer-reported information in surveys, occasionally by crop cuts for a sub-section of a farmer’s plot, and rarely using full-plot harvests. Accuracy and cost vary dramatically across methods. In parallel, satellite data is improving in terms of spatial, temporal, and spectral resolution needed to discern performance on smallholder plots. This study uses data from a survey experiment in Uganda, and evaluates the accuracy of Sentinel-2 imagery-based, remotely-sensed plot-level maize yields with respect to ground-based measures relying on farmer self-reporting, sub-plot crop cutting (CC), and full-plot crop cutting (FP). Remotely-sensed yields include two versions calibrated to FP and CC yields (calibrated), and an alternative based on crop model simulations, using no ground data (uncalibrated). On the ground, self-reported yields explained less than 1 percent of FP (and CC) yield variability, and while the average difference between CC and FP yields was not significant, CC yields captured one-quarter of FP yield variability. With satellite data, both calibrated and uncalibrated yields captured FP yield variability on pure stand plots similarly well, and both captured half of FP yield variability on pure stand plots above 0.10 hectare. The uncalibrated yields were consistently 1 ton per hectare higher than FP or CC yields, and the satellite-based yields were less well correlated with the ground-based measures on intercropped plots compared with pure stand ones. Importantly, regressions using CC, FP and remotely-sensed yields as dependent variables all produced very similar coefficients for yield response to production factors.

This paper is a product of the Development Data Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at tkilic@worldbank.org.

_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 views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
and 135 maloti (approximately $13.5) for women.

The choice to condition the incentives on syphilis and trichonomiasis status was based on the relatively high prevalence of these two STIs in Lesotho and the fact that they are curable and rapid test technologies are available, practical and affordable. Both STIs have high co-infection rates with HIV (Johnson and Lewis, 2008; Kalichman, Pellowski and Turner, 2011). Conditioning incentives on curable STIs also allowed individuals testing positive at one round to be eligible to win in the following rounds. It also allowed inclusion of HIV positive individuals in the trial, which was deemed important for both ethical and epidemiological reasons. Risk reduction among HIV positive individuals may have higher impact on HIV transmission in the community than that of HIV negative individuals.

The short time interval between lottery rounds was chosen in order to bring the benefits of safe sex closer to the present, which may be important if many individuals have high discount rates or a limited horizon (Oster, 2012).

The primary study outcome was HIV incidence.<sup>3</sup> The trial is registered at ClinicalTrials.gov (NCT01589965). The study protocol was approved by the Ethic Committee of the IRCCS Foundation (June, 2009) and by the Ministry of Health and Social Welfare, Lesotho (August 2009).

# **2.4 Participation and trial implementation**

Inclusion criteria consisted of males and females, aged 18-32 years, residing in 29 rural and peri-urban villages across 5 districts in Lesotho. Both HIV-positive and HIV-negative individuals were eligible to enroll. Participation was voluntary but a variety of channels were used to maximize the interest in the project and boost participation. First, a community liaison officer from the implementing NGO visited each participating community before the beginning of the project to garner support from village leaders. Second, media channels were utilized in the form of radio announcements through the most popular local radio stations. Third, posters advertising the project were put up in visible places to inform about the project. Approximately 40% of the age-eligible population in the targeted villages agreed to participate in the study. In total the various procedures yielded a baseline study sample of 3,427 individuals, of which 3,029 (88.4%) completed baseline interview and tests for syphilis, trichonomiasis and HIV.

> 3HIV incidence is considered to be a more accurate measure than HIV prevalence of the state of the epidemic and of current sexual behaviors (Fishbein and Pequegnat, 1999; and Pettifor et al., 2012). HIV prevalence measures the stock of seropositive individuals and is affected both by HIV incidence – the flow of individuals who become HIV infected – and the mortality rate.

6
**Table 14. Standardized effects of the determinants of occupational attainment. Youths from 18-35** **<u>years of age of ENCEL 2017. Comparison by sex.</u>**

|Variables|F<br>|emales<br>Effects|Male<br>Effec|s<br>ts|Groups<br>Comparison|
|---|---|---|---|---|---|
|Social origin on occ<br>|upatio|nal attainm|ent|||
|Direct effect|-||-|||
|Indirect effects|**0.27**|***|**0.19**|***|***|
|Via education||0.12 **|-0.52|ls|*|
|Via education and cognitive abilities||0.03 *|0.03|*|**ns**|
|Via education and first employment||0.13 ***|0.68|ls|*|
|Total effect (direct + indirect)|**0.27**|***|**0.19**|***|***|
|<br>Provider’s cognitive abilities<br>|on o|ccupational|attainmen|t||
|Direct effect|-||-|||
|Indirect effects|**0.04**|*|**0.04**|*|**ns**|
|Via youth’s cognitive abilities||0.04 *|0.04|*|**ns**|
|Total effect (direct + indirect)|**0.04**|*|**0.04**|*|**ns**|
|<br>Youth’s cognitive abilities<br>|on oc<br>|cupational a<br>|ttainment<br>|<br>||
|Direct effect|**0.1**|*|**0.1**|*|**ns**|
|Indirect effects|-||-|||
|Total effect (direct + indirect)|**0.1**|*|**0.1**|*|**ns**|
|Education on occupational attainment||||||
|Direct effect|**0.21**|**|**-0.96**|ls|*|
|Indirect effects|**0.27**|***|**1.31**|ls|***|
|Via youth’s cognitive abilities||0.05 *|0.05|*|**ns**|
|Via first employment||0.23 ***|1.26|ls|*|
|Total effect (direct + indirect)|**0.48**|***|**0.35**|***|**ns**|
|First occupation to occupational attainment||||||
|Direct effect|**0.34**|*|**1.34**|ls|*|
|Indirect effects|-||-|||
|Total effect (direct+indirect)|**0.34**|*|**1.34**|ls|*|
|Levels of significance *** p<0.001, ** p<0.01, * p<0.05. Source|: Own|elaboration fro|m ENCEL 2|017 (n=|3,310).|

Regarding the ethnic origin, differences between indigenous and non-indigenous in three paths (  1,  2, and  3) were observed (see figure 4). In the indigenous group, compared with the non-indigenous, the provider’s cognitive abilities have a weaker effect on the youth’s cognitive abilities, social origin influences the youth’s education with slightly more strength and the latter with greater magnitude on the youth’s cognitive abilities. Overall, this appears to indicate that indigenous youths experience a slightly less influence from the ascribed factors on their cognitive abilities and more on their education.

46
# 1. **Introduction**

Since the beginning of the 1970s, governments of developed and developing countries have enacted or amended a large number of environmental laws and regulations often directed at controlling the industrial emissions of air and water pollution. However, imposing a ceiling on a plant's emissions does not necessarily imply that emissions will fall and environmental quality improve. For the objectives of the regulation to be attained, the behaviour of the regulated community has to be monitored, and compliance with environmental standards has to be enforced.' While a large amount of resources is typically devoted to designing environmental regulations, and negotiating environmental standards with the regulated industries, it is generally acknowledged that resources devoted to monitoring and enforcement are insufficient relative to the complexity and extent of the task.<sup>2</sup> While the monitoring of industrial polluters and the enforcement of compliance are both crucial components of a credible regulatory program, monitoring and enforcement issues have attracted little research effort. In a recent survey of the environmental economics literature, Cropper and Oates (1992) write: "The great bulk of the literature on the economics of environmental regulation simply assumes that polluters comply with existing directives." Moreover, most of the literature on these issues has been of a theoretical nature.<sup>3</sup> On the empirical front, two broad questions have partially been addressed. A first question pertains to the impact of the regulator's behavior on the environmental performance of polluters. In particular, Magat and Viscusi (1990; henceforth MV), and

- X We define monitoring as the process of verifying the firm's status of environmental performance (e.g. compliance), and enforcement as the undertaking of actions (e.g. fines) to bring the firm to improve its environmental performance (e.g comply with environmental standards).

- 2 Among others, see Russell (1990) and O'Connor (1994) for more details.

- _3_ See Downing and Watson (1974), Harford (1978), Linder and McBride (1984), Russell et al. (1986), Beavis and Dobbs (1987), Harrington (1988), Malik (1990), and Russell (1990). For a recent survey of the literature on monitoring and enforcement, see Cohen (1998).

4
21 Administration programs have become heavily subsidized because the loans are made at rates fixed by Congress, irrespective of market interest rates. These programs have led to both more capital-intensive methods of production and to lower utility rates.

The empirical results on the effectiveness of agricultural credit are mixed. Gale's analysis shows a sizable increase in the share of credit going to the farm sector due to agricultural credit policies, in the order of 50% or more. Gale uses the elasticity estimates from a study by LeBlanc and Hrubovcak (1986)'9 which shows that a 1 percentage point reduction in the interest rate increases the demand for agricultural equipment and structures about 1 percent and the demand for land nearly 2 percent. The implications are that loan subsidies primarily are an income transfer to current landowners. Gale estimates that the interest rates charged farmers are about 4 percentage points below what they would be in the absence of subsidies. The LeBlanc and Hrubovcak study suggests that the additional agricultural credit may not have been that effective in generating output growth. An increase in demand for an inelastically supplied factor does not change resource allocation. However, other evidence supplied by Calomiris, Hubbard, and Stock (1986)2 indicates that farm output is affected positively by the value of farm real estate and negatively by the projected debt service burden and number of bank failures. Each of these variables represents a credit constraint. As collateral values rise, farmers can borrow more, raising output. As debt service burdens and bank failures rise, credit to farmers becomes constrained, constraining output. Thus, the Calomiris, Hubbard and Stock paper suggests a stronger link between credit and output than found by LeBlanc and Hrubovcak.

I9Michael LeBlanc and James Hrubovcak, "The Effects of Tax Policy on Aggregate Agricultural Investment," American Journal of Agricultural Economics, 68, November 1986, pp. 767-77.

"Charles W. Calomiris, R. Glenn Hubbard and James H. Stock, "Growing in Debt: The 'Farm Crisis'and Public Policy,"Brookings Papers on Economic Activity. 1986 (2), pp. 441-79.
Table 36

|Dependent variable: Fi|scal adjust|ment when|needed b|ased on Esc|olano et al|.(2014)|||
|---|---|---|---|---|---|---|---|---|
|Variables|(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|Rigid expenditure|-0.085|-0.117|-0.082|-0.161|-0.127|0.710|-0.551|-0.481**|
|(% of GDP)|(0.097)|(0.133)|(0.112)|(0.162)|(0.255)|(0.493)|(0.389)|(0.237)|
|**Economic factors**|||||||||
|GDP growth (t-1)||-1.308||1.757|2.106|3.416|2.141|1.373|
|||(7.427)||(8.017)|(8.324)|(8.739)|(8.525)|(8.293)|
|Inflation (t-1)||20.772*||25.758**|25.280**|27.675**|20.914|28.117**|
|||(10.786)||(12.509)|(12.744)|(13.258)|(12.981)|(13.476)|
|U.S. Interest rate||-0.768**||-1.130***|-1.134***|-1.322***|-1.292***|-1.374***|
|||(0.307)||(0.421)|(0.422)|(0.451)|(0.458)|(0.483)|
|**Political factors**|||||||||
|Gini|||0.070|0.089|0.094|0.626*|0.089|-0.026|
||||(0.127)|(0.278)|(0.278)|(0.341)|(0.270)|(0.184)|
|Rule of law|||-1.195|1.231|1.223|1.426|-1.258|1.753|
||||(0.735)|(1.120)|(1.115)|(1.154)|(2.405)|(1.259)|
|Margin of Majority|||4.471|3.348|3.417|5.389|4.741|-13.440|
||||(3.234)|(3.620)|(3.655)|(4.026)|(3.992)|(9.192)|
|Election's year|||-0.697|-0.480|-0.459|-0.316|-0.325|-0.428|
||||(0.512)|(0.550)|(0.563)|(0.576)|(0.570)|(0.581)|
|**Interactions**|||||||||
|EMEs * Rigidity|||||-0.058<br>(0.346)||||
|Gini * Rigidity||||||-0.021*<br>(0.013)|||
|Rule of law * Rigidity|||||||0.090<br>(0.077)||
|Majority * Rigidity||||||||0.592*<br>(0.317)|
|Observations|111|110|98|97|97|97|97|97|
|Number of ifscode|21|21|18|18|18|18|18|18|
|Country FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|r2_p<br>Standard errors in pare<br>*** p<0.01, ** p<0.05,|0.0103<br>ntheses<br>* p<0.1|0.160|0.102|0.238|0.239|0.272|0.255|0.278|

- 65 -
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began: the World Bank Regional Operations Committee (ROC) decision meeting date, which is the formal corporate review deciding whether or not to proceed with a proposed operation; the Board approval date when the project is officially approved by the World Bank, and the project effectiveness date when the country has met all the necessary conditions needed to begin receiving the funds from the World Bank. The actual length of time from project conception to the first matching grants being given out is substantially longer, involving both preparation time before the ROC decision meeting, and time taken to launch the program and receive applications after project effectiveness. Given that the ideal time to begin an impact evaluation is early in the preparation process, and certainly before Board approval, it can easily take two years from the time when work begins on impact evaluation design to the time when the first grants are given out to businesses.

# **3.1.Why is Impact Evaluation Important for These Projects?**

In discussing these projects with World Bank operational staff and with governments, there was in some cases a sense that these were tried and tested policies that were politically popular, so there was no need for rigorous evaluation.<sup>6</sup> However, in other cases there was genuine skepticism as to whether these grants really did provide benefits beyond the firms that received them, and concern over the costs of implementation. Phillips (2002) provides figures on the implementation costs of earlier matching grant projects in Africa, noting that they ranged from 19 percent of the amounts given out in Mauritius, to 40 percent in Kenya and 54 percent in Uganda. Moreover, these figures excluded some key costs, such as the costs of setting up project committees to evaluate the applications to the matching grant program. Therefore the full costs are relatively high compared to the amount of matching grant funds given out. Given that the resources originate in a World Bank loan that eventually needs to be repaid, citizens of these countries could therefore be paying to subsidize relatively well-off business owners with little public benefit in return.

We also discussed the point that the purpose of the impact evaluation is not just to learn whether the program works or not, but to help improve the future operation and targeting of such programs if we can learn what types of businesses the program works for. As Biggs (1999) notes, ideally matching grant programs should select projects with large economic and social returns to the country that would not otherwise find private funding – but in his direct questions to recipients of an earlier

> 6 Note that all World Bank projects are required to include project indicators and some form of evaluation, but at most these typically measure the number of firms receiving grants and sometimes before-after changes for the recipients captured through surveys of beneficiaries.

12
_Table 3 Summary statistics across treatment groups. Housing values do not include data on rent. All values are in 1000 VND and are annual per capita values._

||(1)<br>T1: 7-day<br>one-line<br>recall|(2)<br>T2: 7-day<br>individual<br>diary|(3)<br>T3: 7-day<br>individual<br>recall|(4)<br>T4: 7-day<br>HH<br>bounding/<br>salience|
|---|---|---|---|---|
|**_Total spending_**|||||
|Total spending|63,824|64,747|64,908|66,623|
|Total food spending|26,971|28,799|28,766|28,575|
|**_Food spending: Breakdown_**|||||
|At-home spending (inc. takeaway)|22,262|20,272|22,086|20,931|
|FAFH food spending|5,709|8,527|6,680|7,644|
|**_FAFH per capita: Breakdown_**|||||
|FAFH food spending (in HH<br>members)|4,051|8,255|6,374|7,339|
|FAFH food spending (in HH<br>adults)|.|7,555|5,689|6,614|
|**_AH per capita: Breakdown_**|||||
|Takeaway food spending|.|631|605|635|
|**_Miscellaneous spending_**|||||
|Total education spending|5,774|5,650|5,146|6,160|
|Total health spending|3,166|3,299|3,467|3,237|
|Total housing spending|3,460|3,262|3,373|3,349|
|Total durable spending|8,581|9,052|8,500|9,345|
|**_Observations_**|478|473|477|476|

# **4. Main results**

Our basic estimating equation is as follows: where Dih is a dummy indicating treatment group i ε {1,3,4} `.` The diary treatment T2 is excluded (i≠ 2) and serves as the benchmark. Household h is assigned to one of the four treatment arms and has outcome 16