rafmacalaba/data-use-mentions-extended huggingface dataset:
firms primarily innovate to create new goods.

Table <u>9. Percentage of innovativeness (% of all firms)</u>

||**Bangladesh**|**Pakistan**|**India**|**Nepal**|**SAR**<br>**average **|<sup>**ECA**</sup>|<sup>**Africa**</sup>|
|---|---|---|---|---|---|---|---|
|New to Firm|44%|8%|54%|12.3%|30%|18%|25%|
|Of which new Product|20%|38%|56%|0%|29%|74%|68%|
|Of which product upgrade|80%|62%|44%|100%|72%|26%|32%|
|Imitator(new to firm/local market)|37%|6%|47%|12%|26%|10%|20%|
|New to National|4%|2%|4%|0.3%|3%|6%|3%|
|New to International|3%|0.5%|2%|0.03%|1%|2%|2%|

Source: Author’s elaboration from Enterprise Survey (2014) In all the SAR region except in Pakistan, process innovation is related to the introduction of a new method, followed by innovations in supporting activities (Table 10). However, a small proportion of processinnovating firms introduce an invention that is new to the market. Again, showing the low degree of innovativeness of SAR firms in terms of vertical innovations. The behavior of the region is similar
assessment of non-experimental measures, there has been much recent debate as to the ability of propensity-score matching methods to obtain better results (e.g. Heckman, Ichimura and Todd, 1997; Dehejia and Wahba 2002; Smith and Todd 2005; Dehejia 2005). The migration example we consider here offers many of the features identified by these studies as conducive to more accurate non-experimental estimation. The nonmigrant control group were administered the same survey instrument as the migrants, including retrospective earnings information, and live in the same villages and work in the same labor markets. Unlike in many labor program settings, there is no substitution bias, as the ability of the controls to migrate other than through the program we consider is severely limited. Moreover, the size of the “treatment” considered here is large and strongly significant. This contrasts with the treatment effect in Lalonde’s NSW male sample of only a 29% increase in earnings (with a t-statistic of only 1.82). Even with these favorable conditions, the non-experimental estimators still overstate the income gains. However, we find that the more recent refinements of propensity-score matching do enable more precision, and provide point estimates which are not statistically different from the experimental estimator.

The remainder of this paper is structured as follows. Section 2 describes the immigration process used as the natural experiment and the sampling method and data from the Pacific Island-New Zealand Migration Study. Section 3 constructs the experimental estimates. Section 4 estimates five different types of non-experimental estimates. Section 5 looks directly at selection, Section 6 considers cost-of-living adjustments and Section 7 concludes.

- 6 -
Asia from 2000 to 2003, the AICD Database applied the same methodology for Sub-Saharan Africa and collected data from 2004 to 2009.

### **(b) Have energy subsidy reforms succeeded in restraining energy consumption?**

To provide an answer to this question the study uses both indicators of energy prices and related consumption. In the case of gasoline and diesel, road sector consumption of fuels is reported, as the transport sector is one of the most intensive users of such fuels. In the case of electricity power consumption is provided:

- **Fossil Fuel Prices** (US$ per liter): Gasoline, diesel and kerosene retail tariff (US$ per liter).

- **Electricity Prices** (US$ cent per kWh) – Residential Average Electricity Tariff level (US$ cent per kWh)

- **Road Fuel Consumption** (kt of oil equivalent per capita): Gasoline and Diesel Fuel Consumption (kt of oil equivalent per capita) by the road sector

- **Power Consumption** (kWh per capita) - Electric power consumption measures the production of power plants and combined heat and power plants less transmission, distribution, and transformation losses and own use by heat and power plants. (kWh per capita)

### **(c) Have energy subsidy reforms managed to avoid adverse social impacts?**

To address this final question, evidence from household surveys on the distributional impact of subsidies by income quintile (or deciles, if available) as well as the materiality of energy subsidies, reporting for each fuel how much income is spent by each quintile of the population is used in the case studies.

- **Expenditure of different energy sources** (what proportion of income poor households spend on each fuel), by quintiles or deciles where available divided by rural/urban areas.

- **Welfare impact of removing energy subsidies, by fuels and/or by quintiles or deciles** (what proportion of poor
and nonhosting districts between the first wave (2009/2010) and the last wave (2011/2012) of UNPS data collection. We do so using our main variables of interest (household welfare measured by consumption per adult equivalent, individual labor market outcomes, household nonagricultural income and output) and some control variables (socio-demographic characteristics). Tables 1 presents the comparison over socio-demographic characteristics at

> 5 The updated UNHCR annual aggregates (Figure A2; Appendix) only include Kampala totals from 2009 to 2016. 6Indeed, the household ID format has been modified for the last 2 waves, a change that complicates the matching across waves. Balancing the panel across all five waves of the longitudinal survey results in a significant drop in the number of enumeration areas/clusters from 320 to 211. The number of households also drops from 2,462 interviewed across the first 3 waves to 1,431 households interviewed across the 5 waves. Attrition is too much of a concern for robust inference.

11
# Appendix B. Comparison to External Conflict Data

## B.1.   Time distributions

The conflict data is measured as a recall question in 2017, dating back to 2010. Therefore, we are wary of the possible bias in measuring such sensitive information. Events that have occurred further in the past might be harder to remember. To address the recall bias, we have compared the victimization data against an externally available data source, the ACLED database on fatalities and conflict events, which is frequently updated with information gathered from newspapers and similar external records. Figure B.1 displays the distribution of fatalities over time across the three different data sources for the North East, the North Central, and the South South. The y-axis thus denotes the share of deaths per year for each data set over the six-year period. For example, of all fatalities recorded in the ACLED database between 2010 and 2016, about 5 percent occurred in 2010. We are comparing the time intensity of the events instead of comparing the number of events because the numbers of events in the two data sets are not comparable.

vii
photovoltaic modules and lithium-ion battery cells. In this link of the supply chain, value added comes from assembling components into a marketable product that customers value.

**Table 5: Number of HS 6-digit products by value chain and segment**

|VC|Raw Materials|Subcomponents|Processed|End products|Total|
|---|---|---|---|---|---|
|EV|9|43|32|5|89|
|Solar|13|53|22|1|89|
|Wind|5|44|55|3|107|
|Total|27|140|109|9|285|

# 4.2) Description of data sources

Bilateral export flows for 226 countries in 5,000 HS 6-digit products (HS 92 nomenclature) between 1995-2021 come from the BACI international trade dataset, reported by the Centre d’Etudes Prospectives et d’Informations Internationales (CEPII). Gaulier and Soledad (2010) reconcile declarations of the exporter and the importer in the United Nations Commodity Trade Statistics Database (COMTRADE). To smooth out data anomalies such as re-exports and focus on structural patterns, we take 5-year rolling averages of export data. Where 5 years of export data for country-product cells is not available, we take the average over the number of available years.

For the regression analysis, we define control variables - GDP per capita, exports (of goods and services) to GDP ratio, C02 emissions and population - from the World Bank World Development Indicators (WDI), available from <u>https://databank.worldbank.org/source/world-development-indicators.</u>

# 4.3) Key metrics

## _4.3.1) Hirschman-Herfindahl Index_

To study market concentration in products associated with decarbonization technologies, we compute the Hirschman-Herfindahl Index (HHI) for each HS 6-digit product p.<sup>6</sup> It is defined as
Asian destinations includes: India, Indonesia, Korea, Japan, Philippines, Singapore, Pakistan and Thailand.

> 11This figure is based on BACI dataset and French customs dataset (1999-2005). To make the figure clearer the outliers observations are excluded. Similar figures for the alternative competition measures are available upon request.

> 12 Export information is collected in the following way: exports outside EU are reported if firms’ annual trade value exceeds 1,000 Euros or a weight of a ton.

> 13 The source of MFN applied tariffs is TRAINS: http://unctad-trains.org.

14The BACI dataset is provided by the CEPII and constructed based on COMTRADE dataset from the UN. This dataset provides bilateral trade flows at the 6-digit product level (Gaulier and Zignago, 2010). From BACI dataset we take information on import flows in each of our destination country. BACI is downloadable from http://www.cepii.fr/anglaisgraph/bdd/baci.htm.

15We thank two anonymous referees for suggesting these two alternative measures of foreign competition (ii) and (iii).

16The assumption behind this measure of extensive margin competition is that equal HS6 varieties imported from different countries are perfect substitutes. This idea has been recently discussed by the trade literature on quality (e.g. Khandelwal, 34
FE|Yes|Yes|Yes|Yes|
|Observations|3,687|3,687|3,687|3,687|
|Number of individuals|1,609|1,609|1,609|1,609|

_Notes:_ *** p<0.01, ** p<0.05, * p<0.1. Results in Columns (1) and (2) are presented as marginal effects. Standard errors in parentheses are clustered at the individual level. Control variables include age group dummy variables, marital status, household size, language skills (listening, speaking, reading, and writing), residence area, and home ownership. Mental health scores are the sum of the 6- item Kessler Psychological Distress Scale (K6), with a higher score indicating worse mental health. The critical value of the F-test from Stock and Yogo (2005) is 16.38.

36
revenues (Prud'homme, 1998) Private investment may also be skewed toward cities, through the existence of "financial urban bias." Evidence from developing countries shows that urban areas tend to be net users of credit, whereas rural areas tend to be net depositors - money is saved by people in rural areas but then borrowed by firms or individuals in urban areas (Chandavarkar, 1985). This "financial urban bias" may exist because of a relatively higher degree of credit rationing in rural areas: transaction costs are high, monitoring is difficult, and average balances are small. The result may be a skewing of investment towards cities, if money is saved in rural banks but lent through urban banks to be invested in urban firms for rates of return that are no higher than those that could be obtained in rural areas.

One important goal of the structural adjustment policies undertaken by developing countries during the past two decades has been the reduction of these elements of "urban bias," by liberalizing agricultural commodity prices, realigning exchange rates, and reducing import barriers to force industrial products to compete internationally. Whether because of general economic decline triggering falls in formal employment, or simply structural adjustment reducing rents to an urban elite, Jamal and Weeks (1998) maintain that, in Africa, "the income gap between urban wage earners and the rural population has narrowed considerably" since the mid-1970s. In fact, their study of four African countries found that "the primary dynamic distributional relationship in Africa has been 8
I POLICY **RESEARCH WORKING PAPER** 1663

# **Summary findings**

One of the best documented empirical facts in economic research has been the positive relationship between internal finance and cash flows - the sum of retained - earnings and depreciation and capital expenditures and investment. But disputes about the analytical basis for the cash flow theory have been largely unresolved.

There are two distinct approaches to the cash flow theory of investment: the managerial and informationtheoretic approaches. The premise of the managerial approach is that managers are primarily interested in maximizing the growth rate of the firm. The premise of the information-theoretic approach is that managers try to maximize shareholder value.

Using a panel of U.S. manufacturing firms (1972-90), Samuel tries to distinguish between these two approaches on the basis of observed firm characteristics. The results suggest that firms rely on internal finance for capital expenditures because of managerial considerations rather than information-theoretic considerations.

The principal shortcoming of the informationtheoretic approach is its reliance on dividend practices as the decisive criterion for studying firm heterogeneity. But dividend practices are incapable of distinguishing between managerial and information-theoretic approaches since both approaches predict a negative relationship between dividend payout ratios and capital expenditures.

But one can distinguish between managerial and information-theoretic approaches using such variables as size, exchange listings, and the ratio of R&D to sales and make contrasting predictions about the firm's reliance on internal finance for capital expenditures.

The evidence shows that the firm's observed reliance of capital expenditures on internal finance is driven by managerial rather than information-theoretic considerations.

While no current research directly distinguishes between managerial and information-theoretic approaches, preliminary evidence seems to favor the managerial approach. And even though the stock market may play a limited role as a source of finance, policy initiatives to reform the financial sector and develop capital markets are likely to enhance the overall efficiency of the resource allocation process in the economy.

This paper - a product of the Operations Policy Group, Operations Policy Department - is part of a larger effort in the department to.
bill). Over the same period, the profit rate in the state sector has fallen from around 20% in 1980 to 6.9% in 1996.

The second factor has been the relative slow improvement in the state sector's technical efficiency (Chai, 1994; Woo et al., 1994). This was mainly related to increased price competition from the non-state sector, in particular, the autonomous township and village enterprises (TVEs) which has eroded profit margins (Jefferson, Rawski and Zheng, 1992). A recent study (Raiser, 1997) using enterprise level data for various ownership forms from four coastal cities shows that the profitability decline in the SOEs is mainly related to growing competitive pressures from the non-state sector are responsible for the erosion of profit rates in Chinese industry.

Since non-state enterprises in China-in particular, the TVEs-have become an increasingly important economic sector outside state-planned production, much attention has been given to comparisons of performance between the state and non-state sectors. Most of these studies focused on total factor productivity (TFP) growth to examine if enterprise reforms have initiated efficiency improvement in SOEs. Existing comparative work include Jefferson, Rawski and Zheng (1989, 1992, 1994, 1996) and Wu (1993, 1995, 1996). These studies reveal that productivity in both the state and non-state industry has risen in recent years. However, the performance of SOEs in terms of output has been much worse than that of the non-state firms.

When studies compare TFP growth across ownership categories, the results reveal that the higher rate of output growth in collective owned enterprises (COEs) and the TVE sector was largely due to the higher rate of TFP growth in the non-state sector. For example, Wu and Wu (1993) 6
poorest 40 percent of population. The use of public health centers as distribution centers for food stamps was found to be central for FSP's better targeting outcomes.

However, despite these targeting outcomes, it is not clear how effective the level of the benefit has been in reducing poverty. The existence of comprehensive panel datasets on the living conditions of Jamaican households during a period of economic reform and FSP experiment, provides an opportunity for an evaluation of the poverty impact of the FSP. This study is an attempt in this direction.

The paper begins with a brief overview of the economic trends leading up to the devaluation of the Jamaican dollar in the early 1990s, followed by a description of the Jamaican food stamp program. The next section outlines the methodology; and final sections present some empirical results and conclusion.

# **2 The Policy Context**

Jamaica's policy reform efforts span over fifteen years and has yielded mixed results. The oil shocks of the early 1970s coupled with the decline in prices of bauxite-the major export crop-resulted in a decline in real GDP and labor income between 1973 and 1980. In order to minimize the adverse consequences of a decline in income, the government increased public expenditures on social services, expanded employment in the public sector, increased the money supply and real wages. As a result, government expenditure as a percent of GDP increased from 25 percent in 1972 to 46 percent in 1976 and the fiscal deficit increased from 5 percent to 24 percent of GDP. By 1977, the governnent allowed real wages to decline and turned to subsidies to mitigate the adverse effects of reform. The share of subsidies in national disposable income increased from 2 2
32

# **5 Concluding remarks**

Green Revolution type technologies such as agro-chemicals and mechanization are being promoted in Africa to raise smallholder labor productivity, specialization and greater market orientation. This in turn fosters Africa’s structural transformation through the productive release of agricultural labor (Beegle & Christiaensen, 2019). Yet, input adoption and mechanization in Sub-Saharan Africa remain limited (Sheahan & Barrett, 2017) and studies have started to question whether the adoption of intensified agricultural production methods is indeed profitable (Burke et al., 2017; Liverpool-Tasie et al., 2017). When adopted, inputs and mechanization are furthermore rarely applied in combination, thereby foregoing possible synergetic effects, possibly one of the reasons for their limited adoption.

Using cross-sectional data collected from rice farmers in Côte d’Ivoire and instrumental variable techniques to control for endogeneity in the adoption of different technology packages, this paper investigates to what extent rice intensification affects farm performance, specialization, market orientation and food security of smallholder rice growing households. Rice intensification is measured through four production packages, compiled through different combinations of available labor saving technologies such as using a tractor or draught animals for land preparation, chemical fertilizer for soil fertility, and herbicides for weeding. Using available information about labor inputs across activities, by age, gender, and type (family/hired), the implication for employment (number of jobs, type of employment (self-versus wage-)), and worker characteristics (adult/child, male/female) is further reviewed in detail, including the agricultural activities through which the changes occurred.

Results indicate significant positive effects of the adoption of more intensive production packages on land and labor productivity, as well as the return to labor, which increases more than
and meteorological sources, that comprise droughts, earthquakes, floods, storms, and temperature extremes in more than 100 countries for over 30 years.<sup>1</sup> The disaster index exploits physical measures of disaster intensity: precipitation, Richter scale, wind speed, and temperature. As such, it is more suitable for estimating causal relations between natural disasters and economic variables. Other databases (EM-DAT, NatCatSERVICE, and similar) contain disaster indicators that are functions of economic development and, therefore, may lead to biased estimates (Felbermayr and Groeschl, 2014).

More particularly, the weather variation represents the difference in monthly rainfall in mm, defined as the proportional deviation of total monthly rainfall from average monthly rainfall of the entire available period. Flooding events are measured by the positive difference in total monthly precipitation, while droughts are indicated with the dummy variable. It is equal to one if at least three subsequent months have rainfall below 50 percent of the long-run average monthly mean, or if at least five months within a year have rainfall below 50 percent of the long-run monthly mean, and zero otherwise. The database uses the maximum realization within a single earthquake event as the measure of the physical disaster intensity of that earthquake. Similarly, the maximum total wind speed in knots on a country basis is their disaster intensity measure for storms. Temperature extremes are measured as the percentage difference between the maximum temperature in one month from the corresponding long-run monthly mean. Strong positive deviations are interpreted as heat waves, while strong negative ones are defined as cold waves.

The overall disaster index uses the inverse of the standard deviation of a disaster type within a country over all years as precision weights to assure that no single disaster component dominates the movement of the whole index. Furthermore, as the impact of a given disaster on the economy of a country clearly depends on the disaster intensity relative to the overall size of the country, the authors scale all respective disaster variables by land area, as suggested in Skidmore and Toya