rafmacalaba/datause-encoder-data huggingface dataset:
-31-

# FIGURE 6 PROJECT OEFINITION

<!-- Start of picture text --> COOE<br>Objectives:<br>Measures of efficiency:<br>Generation of alternatives: (Oescribe the alternatives considered)<br>Alt. 1<br>Alt. 2<br>Alt. 3<br>9Alt 4.<br>Alt. 5<br>Evaluation of alternatives:<br>'Selection of alternatives:<br>Notes:<br><!-- End of picture text -->
|ator<br>Findings<br>Range of estimates<br>Details|**_ng standards_**<br>oyment<br>Decreases<br>Decentralized bargaining associated with lower unemployment.<br>r earnings<br>Mixed evidence<br>Centralized bargaining leads to higher wage growth; decentralized bargaining associated<br>with higher wages for white-collar and lower for blue-collar workers; unions have a positive<br>efect on wages of both unionized and non-unionized workers (spillover efects).<br>r earnings (particular<br>s), labor earnings in-<br>ity<br>Decentralized bargaining associated with higher inequality; unionization rate negatively as-<br>sociated with income inequality.|**_uctivity_**<br>uctivity<br>Mixed evidence<br>If employers have labor market power no efciency efects of unions and collective bargaining<br>r reallocation<br>Centralized bargaining might decrease productivity if it prevents reallocation<br>**_al cohesion_**<br>l cohesion<br>Increases<br>Multi-employer bargaining at sectoral or national level is most inclusive.|**:** The category _Labor earnings (particular groups), labor earnings inequality_ includes both earnings inequality and efects on specifc groups. The category _Prices_ includes debt.|
|---|---|---|---|
|Indic|**_Livi_**<br>Empl<br>Labo<br>Labo<br>group<br>equal|**_Prod_**<br>Prod<br>Labo<br>**_Soci_**<br>Socia|**Notes**|

61
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- [9] Erceg Christopher J., Dale W. Henderson and Andrew T. Levin. 2000., Optimal Monetary Policy with Staggered Wage and Price Contracts. Journal of Monetary Economics 46 (2): 281313.

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- [17] Hausman, Joshua K. 2016. "Fiscal Policy and Economic Recovery: The Case of the 1936 Veterans' Bonus." American Economic Review, 106 (4): 1100-1143.

- [18] International Monetary Fund. 2020. Fiscal Monitor (2020 April) Chapter 1: Policies to Support People During the COVID-19 Pandemic.

- [19] Johnson, David S., Jonathan A. Parker, and Nicholas S. Souleles. 2006. "Household Expenditure and the Income Tax Rebates of 2001." American Economic Review, 96 (5): 1589-1610.

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40
# **<u>References</u>**

Aborode, A. T., Ogunsola, S. O., & Adeyemo, A. O. (2021). _Perspective Piece A Crisis within a Crisis : COVID-19 and Hunger in African Children_ . _104_ (1), 30–31. https://doi.org/10.4269/ajtmh.20-1213 Balboni, C., Bandiera, O., Burgess, R., Ghatak, M., & Heil, A. (2021). _Why do people stay poor?_ https://doi.org/10.3386/w29340 Bassier, I., Budlender, J., Zizzamia, R., Leibbrandt, M., & Ranchhod, V. (2021). Locked down and locked out: Repurposing social assistance as emergency relief to informal workers. _World Development_ , _139_ , 105271. https://doi.org/10.1016/j.worlddev.2020.105271 Bastagli, F., Hagen-Zanker, J., Harman, L., Barca, V., Sturge, G., Schmidt, T., & Pellerano, L. (2016). Cash transfers: what does the evidence say? A rigorous review of programme impact and of the role of design and implementation features. _ODI Report_ , _July_ , 1–300.

www.odi.org/twitter%0Awww.odi.org/twitter%0Awww.odi.org/twitter%0Ahttps://www.odi.org/s ites/odi.org.uk/files/resource-documents/10749.pdf Bhorat, H., Oosthuizen, M., & Stanwix, B. (2021). Social Assistance Amidst the COVID‐19 Epidemic in South Africa: A Policy Assessment. _South African Journal of Economics_ , _89_ (1), 63–81. https://doi.org/10.1111/saje.12277 De La Flor, L., Mujica, I., Fontenez, M. B., Newhouse, D., Rodriguez Alas, C., Sabharwal, G., & Weber, M.

(2021). _Taking Stock of COVID-19 Labor Policy Responses in Developing Countries_ . https://openknowledge.worldbank.org/handle/10986/35331 Fajardo-Gonzalez, J., Gray Molina, G., Mantoya-Aguirre, M., & Ortiz-Juarez, E. (2021). _Mitigating_ _Poverty : Global Estimates of the Impact of Income Support during the Pandemic_ (Development 28
# **IV. Results**

The economic literature presented above argues that regulations can contribute to agricultural development through several channels, many of which are specific to the sector. Among these, they stress efficient input markets, secure water rights, effective rural ICT and transportation services, accessible irrigation systems, comprehensive financial infrastructure and sound sanitary and phytosanitary standards. In order to provide new evidence to this literature we investigate the relationship between regulation and productivity in agriculture.

The first data set used draws from the World Bank’s World Development Indicators (2016) and covers agricultural total output and countries’ stock of human capital. The agricultural total output is measured by agricultural value added in constant 2000 US dollars.<sup>‡‡</sup> The stock of human capital is measured by combining primary, secondary and tertiary gross enrollment ratios. Moreover, figures on main agricultural inputs (labor, land and livestock) are drawn from FAO (2016).<sup>§§</sup> Fertilizer use is measured as the sum of nitrogen, potash, and phosphate content of various fertilizers consumed, in metric tons. Labor is in thousands of economically active population in agriculture. Land is measured as thousands of hectares of arable land and permanent cropland. Livestock is measured in thousands of cow-equivalent livestock units, as calculated by Hayami and Ruttan (1970). To take the effect of climate conditions into account, we add the variable of average annual precipitation in the model. The data of this variable are provided by the WDI database. This variable is presumed to have positive impact on agricultural productivity as in other studies (Weibe, 2003). We use data from CIA (2016) to build a dummy variable for landlocked countries. Previous studies have found this geographical property to have negative impacts on a country’s development (Faye et al., 2004).

Following the approach of Lio and Liu (2008), we estimate country i’s aggregate agricultural production function as: ������� = ��+������������� + ��������� + ������������������ + ��������� + �� (3)

> ‡‡ Converting production value in domestic currency to US dollars may result in a downward bias for products relevant to developing countries. An alternative is using international dollars, but following Antle (1983) we prefer to use US dollars as purchasing power parity-adjusted values might overstate the agricultural production in developing countries. §§ Fertilizer was excluded from the analysis due to its high correlation with EBA indicators. This is due to the presence of several indicators relating to fertilizer regulation among our aggregate measures based on regulatory quality.

15
States in the northern part of the country are yet to adopt the Act<sup>3</sup> . An Act does not automatically address children’s rights and deprivations and improve on conditions unless there are targeted interventions and programs.

But regardless of the Child’s Rights Act signatory status, the Federal Government is working on implementing several policies and interventions to improve on the condition and status of children in Nigeria, including National Routine Immunization Plan, Universal Basic Education Act, National Strategic Health Development Plan, National Plan of Action for Nutrition, Home Grown School Feeding Program, Open Defecation Free Program and Water and Sanitation Policy. All these policies and interventions have focuses to improve the condition of children as well as to improve on different aspects of deprivations studied in this paper. But the big question is whether these efforts are enough to address the poor state of children in Nigeria and have shown any impact on child poverty?

# 3. Methodology

To identify the extent and heterogeneity of poverty, this study analyses child poverty applying both, the World Bank’s monetary poverty definition and a multi-dimensional poverty definition. Irrespective of the poverty measure, individuals below the age of 18 are considered children, as defined in article-1 of the Convention of the rights of the child (United Nations, 1989). Monetary poverty is defined in terms of headcount poverty rate, the proportion of people with income below the poverty line. This is the most commonly used poverty measure (Haughton and Khandker, 2009). For national and international comparison this analysis uses both, the Nigerian national poverty line of 51482.14 Naira a year<sup>4</sup> , as well as the international poverty line of USD 1.90$ a day. Hence, any individual with a per capita household income less than the respective poverty line is considered poor. As common for developing countries with largely informal economies and large shares of the population living on subsistence agriculture, this study estimates household income based on the mean of post-planting and post-harvest consumption. In this case equal weights are assigned to each household member, irrespective of household composition in terms of age and gender.

> 3 <mark>Bauchi, Yobe, Kano, Sokoto, Adamawa, Borno, Zamfara, Gombe, Katsina, Kebbi, and Jigawa (see Adebowale, 2019)</mark>

> 4 This poverty line only applies only to data collected before 2019. In 2019, a new national poverty line of 137,430 Naira per person per year has been established. Given this break in series and the fact that the new national poverty line is composed of slightly different components than the former national poverty line, the analysis refrains from comparing monetary poverty estimates based on the old and new national poverty line.

6
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World Bank (2013). The World Bank Group Goals: End Extreme Poverty and Promote Shared Prosperity. Washington, DC: World Bank.

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______. (2004) _. Aid, Policies, and Growth: Revisiting the Evidence_ . (Working Paper No. 3251). Washington DC: The World Bank.

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______. (2001). Aid and Growth Regressions, _Journal of Development Economics_ , 64(2), 547-70. Harrison, A. (2006). Globalization and Poverty (NBER Working Paper No. 12347). Cambridge, MA: NBER. Higuchi, Y., Ota, K., & Shimpo, K. (2006). Panel Data niyoru Keizaibunseki [Economic Analyses with Panel 24
surveys. Indeed, the results indicate that the HYV adoption rate is significantly lower in areas where the DAP price information is missing. The relative price of DAP over the maize output price also has a negative impact on the HYV maize adoption. Because HYVs use fertilizer intensive technology and require a certain amount of inorganic fertilizer application, a high relative price of DAP is likely discourage the farmers from adopting the purchased HYV seeds more than the price of the HYV seeds itself.

# **4.2. Maize Yield Function**

Next, we present the results from the yield model, separately for Kenya and Uganda in Table 4 and 5, respectively. In each table, we present the results from the three models: the pooled OLS, the household fixed effects model, and the household fixed semiparametric endogenous switching model. In general, all three estimation models provide robust estimates, with a few exceptions. In the pooled OLS model, all the independent variables are interacted with the purchased HYV maize dummy, and we present the total impacts, not the differential impacts, of the interaction terms with the HYV dummy to make comparisons between the pooled OLS and the other models possible. The switching model controls for the household fixed effects as well as the selection between the purchased HYV and the local/recycled HYV maize, as we explained in Section 3.

Because the soil carbon content (measured in the natural log), the nitrogen content of the inorganic fertilizer (100 kg/ha), and the organic fertilizer application (ton/ha) are all interacted with each other and have the squared terms, interpretations of the results could be complicated. Thus, at the bottom of the tables, we present the partial derivative of one input evaluated at the means. We also indicate if the partial derivates are jointly significant.

16
- How does competition, both the number of competitors and the identity of the competitor, influence innovation?

We use a sample of over 19,000 firms in 47 countries, taking measures of firm innovation from firms’ responses to a stratified random survey. The survey also reports data on each firm’s organization and ownership, the type of product market competition it faces, the educational level of its managers and the amount and sources of external financing.

We find that the externally financed proportion of a firm’s investment expenditures is positively related to firm innovation, even after controlling for growth opportunities. Financing from foreign banks has a much larger impact than financing from local banks, both in promoting core innovation of introducing new product lines and technologies as well as other innovative activities related to opening a new plant, and establishing foreign joint ventures and new licensing agreements. Firms are also more innovative if a greater share of their borrowing is in a foreign currency.

Interestingly, we find that state-owned firms are an exception to these findings. State firms that obtain external financing are not significantly more likely to innovate (and in some cases, even less likely to innovate) than those state firms that do not obtain external financing.

These results do not appear to be driven by reverse causality. We find that there is a great deal of heterogeneity in the way external finance facilitates firm innovation. Furthermore, using instrumental variable techniques to deal with the potential endogeneity of external finance leaves the results unchanged.

Firm ownership and legal organization are also important determinants of firm innovation. Privately owned firms are, in general, more innovative than state owned enterprises and those organized as corporations are more innovative than firms organized as proprietorships, partnerships or cooperatives. Identity of the controlling shareholder seems to be particularly important for the introduction of new technology and those private firms whose controlling shareholder is a financial institution are the least innovative.

We also find suggestive evidence for the role of competition in spurring innovation. Firms are more innovative if the firm is an exporting firm. Foreign 3
of the supplementary feeding program from 1998 onward with individual-level data on health and nutritional status of children.

The analysis sample includes all children who were between 6 and 60 months at the time of the 1997 and 2000 survey rounds and lived in IFLS communities (2170 and 2618 children, respectively). The average age of these children in 1997 and 2000 was 34.1 and 32.7 months, respectively. Given the low percentage of communities in which nontargeted groups (older children and adults other than pregnant women) received benefits, the share of non-targeted children exposed to the program is likely to be negligible.

The measure of nutritional status used in our analysis is child standardized height-for-age. In terms of potential measurement error, the health literature suggests that this is a less problematic indicator for child health and nutritional status than other alternative health measures.<sup>14</sup> Moreover, as a longer-term indicator of health status, standardized height-for-age is more suitable for analyzing potential adverse effects of the crisis at the time of the 2000 survey round.

In order to focus on more extreme effects, we also examine the probability that children suffer from stunting, or have standardized height-for-age below negative 2, which is often referred to in the medical literature as _shortness_ . Standardized height-forage is calculated using the STATA ado program _zanthro_ (Vidmar et al, 2004), which compares actual child height for age in the IFLS sample with those from a US reference population from the 2000 Center for Disease Control and Prevention (CDC) Growth Charts.

> 14 In IFLS, height and weight are measured by trained health workers with regularly calibrated health equipment. IFLS enumeration protocols and training helped to limit errors in measurement of this variable.

10