rafmacalaba/datause-encoder-data huggingface dataset:
mentation of an integrated set of policy interventions that take into account the country’s structural deficits, particularly the weak rule of law, and low business confidence in public institutions. A credible commitment to net zero, improvements in access to finance and the rule of law, coupled with a mix of policy instruments, can provide a path to sustainable and equitable economic growth while meeting T ̈urkiye’s climate goals.

# **References**

- Acemoglu, D., Aghion, P., Bursztyn, L., Hemous, D. (2012): The environment and directed technical change, _American Economic Review_ , 102(1), pp. 131–166.

- Adjemian, S., Bastani, H., Juillard, M., Karam ́e, F., Mihoubi, F., Mutschler, W., Pfeifer, J., Ratto, M., Rion, N., Villemot, S. (2022): Dynare: Reference Manual, Version 5, Dynare Working Papers 72, CEPREMAP.

- Albonico, A., Cal ́es, L., Cardani, R., Croitorov, O., Dio, F. D., Ferroni, F., Giovannini, M., Hohberger, S., Pataracchia, B., Pericoli, F., Pfeiffer, P. (2019): The Global Multi-Country Model (GM): An Estimated DSGE Model for Euro Area Countries, European Economy - Discussion Papers 2015 - 102, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.

- An, S., Kang, H., et al. (2011): Oil shocks in a DSGE model for the Korean economy, _Commodity Prices and Markets_ , 20, pp. 295–321.

- Annicchiarico, B., Di Dio, F. (2015): Environmental policy and macroeconomic dynamics in a new Keynesian model, _Journal of Environmental Economics and Management_ , 69, pp. 1–21.

- Argentiero, A., Atalla, T., Bigerna, S., Micheli, S., Polinori, P. (2017): Comparing renewable energy policies in EU-15, US and China: A Bayesian DSGE model, _The Energy Journal_ , 38(KAPSARC Special Issue).

- Barrett, S. (2008): Climate treaties and the imperative of enforcement, _Oxford Review of Economic Policy_ , 24(2), pp. 239–258.

- Barro, R. J., Grossman, H. I. (1971): A General Disequilibrium Model of Income and Employment, _American Economic Review_ , 61(1), pp. 82–93.

- Battiston, S., Monasterolo, I., Riahi, K., van Ruijven, B. J. (2021): Accounting for finance is key for climate mitigation pathways, _Science_ , 372(6545), pp. 918–920.

- Benigno, G., Fornaro, L. (2018): Stagnation Traps, _Review of Economic Studies_ , 85(3), pp. 1425–1470.

29
**Figure 1.  Poverty Headcount Rate, 2001 - 2013**

<!-- Start of picture text --> 100%<br>90%<br>80%<br>70%<br>64.3%<br>60%<br>50% 51.7%50.4%<br>44.1%<br>40%<br>36.8%36.3%<br>30% 29.5%<br>20%<br>10%<br>0%<br>Year Urban Rural Total<br>poverty line<br>Percent of the population under the national<br><!-- End of picture text --> Note: Author’s calculation using PSLM 2001, 2004, 2007 and 2010.

27
_Table 2: Sociodemographic Characteristics of Mexican Population 65 Years Old and Older (2014)_

||2014<br>||
|---|---|---|
||Millions|%|
|Females|4.9|54.5|
|Urban|6.8|74.9|
|Indigenous Language Speakers|0.8|9.1|
|Single household|1.2|13.1|
|Household head|4.6|50.4|
|Without Access to Basic Services in the Dwelling|2.0|21.8|
|Illiterate|2.2|24.1|
|Educational Gap|5.5|60.7|
|Without Access to Food|1.8|20.0|
|Without Access to Health Services|1.2|13.1|
|With a Disability|3.3|36.15|
|**Access to health services, by institution**|||
|Seguro Popular|3.5|44.4|
|IMSS|3.1|39.6|
|ISSSTE|0.9|11.5|
|Other*|0.5|4.5|
|**Total elderly with access to health services**|7.9|100.0|
|**Total adults of 65 years of age and older**|9.1|100.0|

Source: Based on authors’ calculations with the ENIGH-MCS 2014.

* Include health services provided by Pemex, Defensa, Marina, other health services via social security and private health insurance. Note: The mean years of schooling in the period was the following: 2014 (4.7).

# 3.5 Empirical strategy

This paper aims to uncover the Intention-To-Treat effects (ITT) and the Treatment-on the-Treated effects (TOT) of the expansion of PAM on extreme poverty and labor supply of the elderly. The outcome variables of interest in our study are: extreme poverty headcount index, extreme poverty gap index, extreme poverty severity index, multidimensional extreme poverty index, labor force participation, and use of time including work.

To evaluate the impact of the expansion of PAM on the outcomes of interest, having a randomized controlled trial with a sufficiently large sample would allow us to directly estimate the causal effects of the intervention and to minimize bias. However, the actual expansion-of-PAM treatment was not randomly assigned. Even though ENIGH-MCS identifies the self-reported PAM beneficiaries, using this data directly in a regression to estimate the effects of the expansion of PAM on extreme poverty and on labor supply would yield biased estimations due to endogeneity. The endogeneity of the treatment may be a result of the targeting strategy, the prioritizing operational mechanisms of PAM, or the self-selection of beneficiaries. Therefore, we used a quasi-experimental design to evaluate the effects of the expansion of PAM on extreme poverty and labor supply.

The eligible-for-treatment group (from now on the treatment group) are the adults between 66 and 69 years old that were not receiving contributory pensions or retirement payments before and after the change in PAM’s eligibility criteria, and the control group are the non-elderly individuals aged 61 to 64 who are not receiving pensions or retirement payments and who are not eligible to participate in PAM.

13
reputation also decreases.<sup>7</sup> Below, we explore the relation between competition, governance, and firm innovation.

Finally, we also consider the relation between firm size and innovation. Since Schumpeter (1947), there exists a large literature relating the rate of innovation to firm size in developed economies.<sup>8</sup> Below, we explore differences in the rate of innovation across firm size categories in our sample of developing country firms. We also treat firm size as a control variable in our tests of the relation between financial access and governance and the rate of innovation.

In summary, the literature on firm growth and financial development suggests that innovation is likely to be an important channel through which financial development affects growth. Below we test this hypothesis by examining the relationship between firm innovation and external financing, firm governance and product market competition. In our sample, the governance factors that are likely to be important are ownership structure and differences in legal organization, and their interaction with product market competition.

# **3. Data and Summary Statistics**

The World Bank Investment Climate Survey database (ICS) consists of firm survey responses of over 19,000 firms in 47 developing countries.<sup>9</sup> The core survey uses standardized survey instruments and a uniform sampling methodology to benchmark the investment climate of individual economies across the world and to conduct firm performance analyses. The survey also report detailed information on firm employment, age, industry, ownership, legal status, and the number of establishments. The Investment Climate Survey sample from the universe of registered businesses and follow a stratified random sampling methodology.<sup>10</sup>

> 7 See, for example, Maksimovic (1988) or Maksimovic and Titman (1991).

> 8 According to Schumpeter, large firm size is essential for innovation since larger firms can provide economies of scale in production and innovation. Other studies, by contrast, have emphasized the role of small firms including Rothwell and Dodgson, 1994; Acs and Audretsch (1987); and Scherer (1965) to name a few.

> 9 The survey actually covers 44,000 firms in 67 countries. The sample is reduced to 19813 firms in 47 countries after eliminating observations with missing firm-level innovation variables. 10 A detailed description of the sample design and sample frame can be found at

> <u>http://www.enterprisesurveys.org/documents/Sampling_Note.pdf</u> and a detailed description of the

8
**_Trade and FDI._** Trade reforms have brought down tariffs in Africa, and the trade regimes do not discriminate against exports relative to other regions worldwide. However, African exports, particularly non-oil exports, are growing slowly (figure 15). In fact, in sharp contrast to the case for China and for Asia’s top performing countries, exports are not growing in importance in the region’s output and are declining in importance for Africa’s top performers. As a result, Africa’s share of world trade is falling (figure 16). And Africa’s exports remain heavily concentrated compared with those of other regions (figure 17).

Although FDI as a share of GDP has grown since 1990 (see figure 18), the absolute amount is still modest at $13.3 billion in 2006 and is concentrated primarily in one country, South Africa, and in one line of business, extractive industries. Outside of FDI, migrant remittances appear to be increasing, but a large portion of the flows bypass formal financial channels and these remittances are difficult to account for. Exogenous private flows such as these could certainly become important sources of balance of payment finance to supplement and counter the fluctuations of foreign aid. A recent paper by Ratha, Mohapatra, and Plaza (2008) examines the issues and their potentials.

**Table 14: GDP Growth, Investment Rates, and ICOR Select Countries in Asia and Africa, 2000-06**

|**GDP Growth**|**I/Y**|**ICOR**|
|---|---|---|
|**Top Asian Performers**|||
|China<br>9.5|39.7|4.2|
|Cambodia<br>9.2|19.0|2.2|
|Vietnam<br>7.5|33.4|4.5|
|India<br>6.9|27.8|4.7|
|Lao PDR<br>6.4|25.1|4.0|
|**Top African Performers**|||
|(excl. middle inc,, oil & resource intensive ctys)|||
|Mozambique<br>7.6|26.4|3.1(5.1*)|
|Tanzania<br>6.3|20.2|3.3|
|Ethiopia<br>6.2|18.4|3.0|
|Burkina Faso<br>6.1|18.5|3.3|
|Uganda<br>5.6|20.7|3.8|
|Rwanda<br>5.5|19.4|3.7(5.8*)|
|Ghana<br>5.0|25.7|5.2|
|All SSA Ave<br>4.9|20.5|5.5|
|Note: Figures in parenthesis include the flood year 20<br>and drought year 2003 in Rwanda. I/Y = investment a<br>ICOR= incremental capital-output ratio.<br>Source: World Bank WDI and authors’ estimates.|00 in Mo<br>s percent|zambique<br>of GDP;|

**_Accumulation and productivity of capital._** Africa’s growth deficit in the past is also the product of low productivity, not just low savings and investment. Growth

37
Libya, where the food subsidy program is very large. In this country and with a universal transfer designed to offset the poverty gap, the increase in per capita government revenue can be large but still below the overall gains in revenues determined by the reforms.

Figure 10: Governments’ Revenue Impact of a 30 Percent Reduction in Subsidies on Energy Products, in US$-PPP/capita/year <!-- Start of picture text --> Electricity<br>Liquefied petroleum gas<br>Tunisia<br>Tunisia<br>Morocco<br>Morocco<br>Libya Libya<br>Iran, Islamic Rep.<br>Iran, Islamic Rep.<br>Djibouti<br>Djibouti<br>0 10 20 30 40<br>Values in US$‐PPP 0 50 100Values in US$‐PPP150 200 250 300 350 400<br>Per capita equivalent transfer to offset the change in<br>the poverty gap Per capita equivalent transfer to offset the change in the poverty gap<br>Change in the per capita government revenue Change in the per capita government revenue<br><!-- End of picture text --> <!-- Start of picture text --> Gasoline Diesel<br>Tunisia Tunisia<br>Morocco Morocco<br>Libya<br>Libya<br>Iran, Islamic Rep.<br>Iran, Islamic Rep.<br>Djibouti<br>Djibouti<br>0 50 100 150 200 250 300<br>Values in US$‐PPP 0.0 0.5 Values in US$‐PPP1.0 1.5 2.0 2.5 3.0<br>Per capita equivalent transfer to offset the change in<br>the poverty gap<br>Per capita equivalent transfer to offset the change in the poverty gap<br>Change in the per capita government revenue<br>Change in the per capita government revenue<br><!-- End of picture text --> _Source:_ World Bank estimations from Household Budget Surveys.

21
Policy Research Working Paper 10196

# **Abstract**

Large-scale transport infrastructure investment can facilitate structural transformation by changing firm behavior. Although its impact is evident over the long term, an important empirical challenge is potential endogeneity of infrastructure placement. By using the dynamic panel data regression, the paper examines the impacts of massive road corridor investment under the Nurly Zhol program in Kazakhstan. The paper takes advantage of detailed micro shipping data to capture historical changes in transport connectivity over the past 10 years. While the average travel speed has slightly increased, transport costs have been nearly halved. The estimated translog cost functions indicate that local market accessibility is the most important factor to boost firm productivity. The elasticity was 0.24 in absolute terms. Inventory is found to be a major cost factor for firms. It is found that a 10-percent improvement in accessibility to large cities, such as Astana and Almaty, could allow firms to reduce their inventory by 8.7 percent. The market accessibility is found to foster firm agglomerations, but agglomeration economies do not seem to translate into higher firm productivity. This is possibly because the Kazakh economy still lacks effective forward or backward linkages across industries.

This paper is a product of the Transport Global Practice. 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://www.worldbank.org/prwp. The author may be contacted at aiimi@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
is that it includes a better control group for the FVA-controlled HS 4-digit products, whereas the disadvantage is that it covers just a subset of the FVA-controlled products.<sup>54</sup> All columns in Panel B of Table 7 also show an insignificant coefficient on the interaction term. Thus, there is no evidence of differential trends in import growth for food contact materials FVA-controlled products relative to other imported products in the same HS 2-digit chapters before the FVA reform. Hence, we believe that the common trends assumption required for the appropriateness of D-i-D regressions to evaluate the impact of the FVA reform is valid.

Table 8 presents the results from estimating our D-i-D regressions - Equation (5) - by OLS with standard errors robust to heteroscedasticity. Again, Panel A provides results for the full sample while Panel B provides results for a smaller sample limited to food contact materials and the other HS 4-digit products included in the corresponding HS 2-digit chapters. Recall that the D-i-D estimator allows us to examine the question of whether the products for which the FVA has oversight responsibilities saw faster import growth than other products in the period after the FVA reform, relative to the period before the reform.

Focusing first on column (1) in Panels A and B of Table 8, the D-i-D estimates from a simpler version of Equation (5) including only the HS 4-digit product-country of origin (panel) and semester-year fixed effects suggest that the FVA reform led to a significant increase in import values of FVA products, relative to other products in the post-reform period ranging from July 2014 until the end of 2015. Our concern that the impact of the FVA reform could be potentially biased due to foreign supply shocks or import demand shocks in Macedonia correlated with the FVA reform episode led us to include explicit control variables for foreign supply shocks and import demand shocks based on WITS trade data from column (2) onwards. These variables absorb changes in import values that are unrelated to the FVA reform. The controls for foreign supply and import demand shocks result in a decrease in the magnitude and significance of the estimated trade impact of the FVA reform, but the impact in columns (2) and (3) is still significant at the 10 percent confidence level. In turn, note that variation in foreign supply and import demand matters for Macedonian imports: both foreign supply and import demand shocks have significant effects on Macedonian imports, with the expected positive sign.

> 54 Specifically, this smaller sample does not include FVA-controlled products food of non-animal origin products, nor food of animal origin and animal feeds.

35
# **Table 25: DID Regression (11)**

||No. of HH|members engage|d|||||HH Monthly<br>income|
|---|---|---|---|---|---|---|---|---|
||Agricultur|e|Industry|Commerce|Service||Public sector||
|D|-0.201|(0.117) *|0.001 (0.012)|-0.014 (0.036)|0.037|(0.026)|0.221 (0.089) **<br>-|-<br>0.018 (0.091)|
|T|-1.563|(0.157)|-0.022 (0.013) *|-0.076 (0.051)|0.018|(0.027)|0.355 (0.092) ***|0.246 (0.075) ***|
|D*T|0.304|(0.191)|0.023 (0.017)|0.067 (0.055)|-0.010|(0.041)|0.114 (0.119)|0.170 (0.101) *|
|lnHH size|0.923|(0.126) ***|-0.008 (0.017)|0.026 (0.035)|0.052|(0.034)|0.217 (0.071) ***|0.352 (0.062) ***|
|Adult share|1.148|(0.264) ***|0.014 (0.030)|0.015 (0.066)|0.016|(0.060)|0.044 (0.164)|1.372 (0.130) ***<br>|
|HH head sex: Male|-0.925|(0.158) ***|0.007 (0.013)|-0.048 (0.028) *|0.023|(0.037)|0.074 (0.094)|-<br>0.038 (0.074)|
|HH head education:||||||||-|
|Elementary|0.097|(0.107)|0.012 (0.007) *|0.052 (0.021) **|0.027|(0.017) *|0.228 (0.056) ***|<br>0.050 (0.056)|
|HH head education: Secondary|<br>-0.614|(0.211) ***|-0.006 (0.006)|0.265 (0.096) ***|<br>0.053|(0.051)|1.083 (0.179) ***|0.188 (0.098) **|
|HH head education: University|-1.066|(0.349) ***|0.154 (0.156)|-0.075 (0.034) **|-0.041|(0.025) *|2.098 (0.457) ***|0.979 (0.142) ***|
|Appliance ownership:|||||||||
|Refrigerator<br>Appliance ownership: Color|-0.097|(0.155)|-0.017 (0.019)|0.067 (0.037) *|0.037|(0.032)|0.119 (0.104)|0.096 (0.083)<br>-|
|<br>TV|-0.042|(0.144)|0.019 (0.011) *|-0.002 (0.038)|-0.050|(0.040)|0.077 (0.096)<br>|0.005 (0.075)|
|Appliance ownership: Radio<br>Appliance ownership: Gas|-0.114|(0.098)|0.015 (0.007) **|-0.012 (0.029)|-0.013|(0.022)|-<br>0.078 (0.066)|0.022 (0.050)|
|stove|-0.035|(0.124)|0.002 (0.003)|-0.015 (0.023)|0.028|(0.012) **|0.154 (0.075) **|0.136 (0.089)|
|Appliance ownership:|||||||||
|Washing machine|-0.223|(0.143)|-0.006 (0.015)|0.088 (0.056)|0.003|(0.035)|0.164 (0.097) *|0.176 (0.055) ***|
|Gas use for cooking|-0.411|(0.132) ***|0.021 (0.016)|0.138 (0.051) ***|<br>0.043|(0.031)|0.312 (0.093) ***<br>-|0.365 (0.049) ***<br>-|
|Power use for lighting|-0.167|(0.145)|0.010 (0.010)|-0.003 (0.030)|0.065|(0.024) ***|<br>0.115 (0.098)|0.005 (0.078)|
|Tap water for cooking|0.024|(0.103)|0.006 (0.010)|0.020 (0.030)|-0.028|(0.025)|-<br>0.003 (0.067)|0.071 (0.048)|
|Constant|-1.215|(0.408)***|-4.635 (0.049)***|-4.609 (0.100)***|<br>-4.758|(0.101)***|<br>-<br>4.930 (0.253)***|3.906 (0.209)***|
|Obs.|2,064||2,064|2,064|2,064||2,058|1,797|
|R-squared|0.201||0.017|0.036|0.014||0.097|0.227|
|F-stat|36.72||0.24|1.87|1.19||8.42|29.16|

Note: Standard errors are shown in parentheses. *, **, *** indicate the statistical significance at 10%, 5% and 1%, respectively.

44
method for environmental assessment of agricultural land use, which has not been considered in most LCAs. Environmental objectives and indicators of the landuse quality are defined. The method is tested in case studies of cultivated vegetable oil crops: Swedish rapeseed, Brazilian soybean, and Malaysian oil palm. They conclude that soil erosion, soil organic matter, soil structure, soil pH, phosphorus and potassium status of the soil, and the impact on biodiversity are a good choice of indicators of long-term soil fertility and biodiversity impacts of land-use impacts of various cropping systems. Land-use assessment performed in this way includes not only quantitative results but also qualitative descriptions. Lal (2004) provides a comprehensive survey in which he compares the carbon intensity of various agricultural activities and finds plowing, fertilizers, pesticides, and irrigation to be the most carbon-intensive operations. Improved practices like no-till agriculture, improving nitrogen-use efficiency, integrated pest management, and drip irrigation are all found to have lower carbon intensities.

# **2.4 Summary of current literature**

We summarize some of the main findings from the reviewed studies below.

1. The life cycle of ethanol and sugarcane has been the most widely studied. Ethanol from sugarcane offers the highest energy and CO2 benefits, followed by cassava, while ethanol from corn offers relatively modest energy and environmental benefits. Cellulosic ethanol, however, is expected to deliver higher future net energy gains and reduced future GHG.

2. Coproducts have an important bearing on the net energy and environmental benefits. However, there is considerable debate about the most suitable technique for the valuation of coproduct credit.

3. Crop rotation and intercropping are better than monocropping, while perennial crops are better than annual crops for achieving soil carbon sequestration, reducing soil erosion and use of agri-chemicals in the production of biomass.

4. Electricity production from biomass also has the potential to offer significant reductions in fossil-fuel use and GHG. In recognition of the fact that multiple 32
investigate the reason for those extreme values.

We take two decisions to limit the influence of income from this module. First, we topcode individual income from that module, for each year in that period, at the average income + 2 standard deviations - this limits the influence of a few outliers with extreme values each year - in Table F1, we show that less than 1% of individuals each year have agriculture income topcoded in the survey, and also presents the threshold used for topcoding. Nonetheless, the large incomes in those periods are not only driven by a few outliers, but by the entire distribution of agricultural income being shifted upwards. So we include a second adjustment: we first compute the average real agricultural income in the period 2014-2019, after the agricultural module was discontinued, and then crate an adjustment factor for each year in the period 2003 - 2013, such that the amount of real income in each of those years match the average for the 2014 - 2019 period. These adjustment factors, which are applied to each individual agricultural income, vary from .5 in 2011 to .8 in 2005.

Table F1: Topcoding agricultural module

||Share topcoded (%)|Topcode threshold (L)|
|---|---|---|
|2003|0.210|14,476|
|2004|0.241|15,651|
|2005|0.277|17,030|
|2006|0.200|17,980|
|2007|0.239|19,227|
|2008|0.375|21,419|
|2009|0.267|22,597|
|2010|0.281|23,658|
|2011|0.564|25,258|
|2012|0.364|26,571|
|2013|0.143|27,942|

_Note:_ This table presents, for each year in the period 2003-2013, the share of observations for which agricultural income is topcoded and the threshold for topcoding.

# **G Adjusting tax record data for 2003 - 2011**

In Table 1, we document that our dataset includes almost no information on withholding forms for the period 2003 -2010 - in particular, it includes no information on withheld wages, which represent a large share of income observed in the tax data. The reason for that is that withholding forms before 2011 were not electronic and have not 65