rafmacalaba/data-use-mentions-extended huggingface dataset:
<mark>we also discover in our paper for a much broader set of firms across 57 countries. One key advantage of our study compared to Huang et al. (2020) is we could use firm fixed effects to control for unobservable firm characteristics. Huang et al. (2018), using the cross-country Orbis firm database</mark> by Bureau van Dijk, <mark>also document a negative correlation between public debt and corporate investment, especially for industries dependent on external finance. However, the Orbis data is skewed towards large publicly listed firms. Similarly, Dermici et al. (2019) use cross-country Compustat data on publicly listed firms to document a negative relationship between government debt and corporate leverage, an imperfect proxy for investment. Our paper focuses on a larger set of firms with richer information that allows us to take a step further by exploring the distribution effects of high public debt and the channels of the effects (finance and regulatory channels).</mark>

# 2. Data and Econometric Specifications

## 2.1 Data

The main source of firm-level data is the World Bank’s Enterprise Surveys (ES). The standard ES sample collects information on a representative sample of formal (registered) private firms operating in manufacturing or service sectors. The ES data are fully comparable across countries and are collected via face-to-face interviews with business owners or top managers using a global standardized methodology. The survey is implemented using stratified random sampling with location (within country), sector, and size as the strata. The ES universe excludes informal firms (unregistered), fully government-owned enterprises, and micro firms (firms with fewer than five full-time employees). Several quality control checks are employed throughout the survey implementation process. Supervisors and enumerators attend formal training sessions to ensure the best practices are deployed. In addition, consistency checks are employed for 10 percent and 50 percent batches of the data during the survey to allow quick callbacks to respondents to be undertaken when necessary to verify the information.

6
.0|2.8|2.7|0.6|20|0.80|
|Uganda|2.3|3.2|1.3|0.40|92|1.5|1.9|1.6|0.7|62|0.64|
|Zambia|11.2|4.4|4.5|0.39|411|8.3|5.0|8.5|1.1|59|0.75|
|**Average **|**5.8**|**11.2**|**3.9**|**0.48**|**242**|**4.1**|**12.1**|**4.0**|**0.7**|**72**|**0.69**|

Notes: Earnings are in PPP ($,2011). Ratio of medians is the ratio of the median earnings for teachers on a fixed term or temporary contract to that for teachers on a permanent contract. Teachers include survey respondents who self-identified as a primary or secondary school teacher and a wage worker. All teachers have secondary or secondary or post-secondary education. The top and bottom 1% earnings are trimmed. Surveys in The Gambia, Ghana, Liberia, Malawi, and Nigeria did not report whether a worker was on a permanent or fixed term/temporary contract. Source: Surveys listed in Table 1.

40
Table 2: Characteristics of workers in employment and labor income (national level, age 15-64)

||2007|2009|2011|2013|2015|2017|2019|2020|2021|
|---|---|---|---|---|---|---|---|---|---|
|Activity Rate|73|74|74|72|69|70|74|74|72|
|Employment rate|69|72|72|70|67|68|70|68|69|
|Self-employed workers (%)|34|34|35|37|41|42|42|44|44|
|Workers in MSE (%)|33|30|30|26|25|26|27|28|25|
|Workers in public frms (%)|26|25|26|30|25|26|25|27|-|
|Real average monthly income|1,489|1,559|1,672|2,228|2215|2,105|2,124|2,113|2,070|
|Real average monthly income (for self-employed)|1,176|1,365|1,658|1,730|1923|1,644|1,686|1,735|1,490|

_Notes:_ Based on data from EH 2007-2021. We define workers in micro and small enterprises (MSE) for people who are employed in a firm with less than five employees, domestic workers and unpaid workers. Average income is in 2010 prices.

In constructing the index, we rely on the methodology proposed by Del Carpio et al. (2017). Due to data availability and the need for comparability across time, we include a reduced number of components in our study. Furthermore, given the specific focus on
employment increased in 2009, these changes in employment shares understate the actual percentage increases in job creation in these sectors.

The government also took several measures to reduce the employment shock associated with the crisis. Recognizing that small and medium enterprises were not well positioned to cope with crisis-related shocks, the government reduced the tax burden on those enterprises and provided other sources of support. In November 2008, the State Council issued an executive order facilitating extension of credit to small and medium enterprises; and in December 2008, the Ministry of Human Resources and Social Security implemented several measures to reduce burdens on enterprises, including: (1) allowing enterprises facing financial difficulties to delay payment of social security funds; (2) temporarily reducing mandated contributions to medical, work injury, and unemployment insurance; and (3) using unemployment funds to maintain employment levels in firms facing financial difficulties. By the government’s own estimate, these three measures helped save 10 million jobs.<sup>12</sup> Local governments also worked hard to convince enterprises in their jurisdiction to avoid shedding large numbers of workers. According to interviews by the authors with city labor bureau officials in Shanghai in early 2009, firms were offered various sources of support, including wage subsidies and suspension of tax payments, to encourage them to keep local residents employed. Interestingly, the officials were unconcerned about layoffs of migrant workers. These efforts by local governments, in addition to a strong stimulus and supportive national policies, likely mitigated the negative employment impacts of the crisis. Preventing firm employment reductions or outright failures reduced short-term pain but at the potential cost of reducing the creative destruction useful for enhancing competitiveness in the longer term. Implementation of the 2008 Labor Contract Law may also have been influenced by the economic crisis. Although, on average, neither firms nor workers reported that enforcement of the law was less strict after the crisis hit, analysis of the firm data finds that exporting firms subject to 13
associated with an increase of around 10 percent in the value of their country’s FDI stock in that sector over the timeframe of the analysis.

To gauge the relative effectiveness of IPAs, a country-interaction effect with the IPA sectoral targeting coefficient was incorporated into the same PPML model These findings suggest that there is considerable heterogeneity between IPAs in their ability to affect FDI stocks. Overall, 10 countries have positive and statistically significant results (classified as “high performing” IPAs). An additional 13 IPAs have statistically insignificant results, while 3 IPAs have negative and statistically significant results (which are jointly classified as “other” IPAs). Finally, 10 IPAs fell out of the country-interaction equation as they either did not have sectoral targeting or exhibited no variation in the timing of their sector targeting strategy.

The final section compared the 10 “high performing” IPAs to the 16 “other” IPAs across a range of characteristics from the WB-WAIPA survey, and used t-tests to consider which IPA characteristics significantly differ between the two groups. This suggests that effective IPAs are more likely to be private or semi-private agencies. Their mandate also tends to be focused narrowly on foreign investment and exclude responsibilities for domestic investment promotion. Such IPAs are also more likely to have a board of directors, while their staff tends to be better compensated. Finally, high-performing IPAs are also likely to engage in more investor services, partly by engaging smart, sectoral analytics and by adopting systems for identifying investor complaints or disputes.

This paper provides a modest contribution to two distinct bodies of literature. The first relates to economic literature analyzing the impact of IPA to attract FDI. Here, the added value is the paper’s use of a wide set of FDI source countries and actual FDI stock data (rather than FDI announcements). It also explicitly considers how an IPA’s targeting of a priority sector in one country may affect the relative effectiveness of IPAs in _other countries_ targeting the same sector, by including sectoral IPA targeting within a structural gravity model framework
mortality water sanitation<br>rate<br><!-- End of picture text --> _Source:_ Authors’ calculations based on data from the World Development Indicators database. _Note:_ Distance to goal achieved in this graph is a weighted average of the latest indicators, using population weights in 2009.

Behind those aggregate numbers, however, there is a great diversity of performance across indicators, countries, and groups of countries that requires further analysis. Bourguignon et al. (2010), Leo and Barmeier (2010), and ODI (2010) showed that progress has been more heterogeneous than is shown by the aggregate figures. Although the MDGs were conceived as global targets to spur development efforts and support to poor countries, it is necessary to measure and describe progress at the country or other level to better understand advances and remaining gaps.<sup>5</sup> Global and regional summaries typically amass data for countries of dissimilar

> 5 Fukuda-Parr and Greenstein (2010) sustain that development goals are not ―hard planning targets‖ but rather guidelines ―meant to encourage countries to strive for accelerated progress‖. Their approach consists in comparing rates of change in development indicators before and after 2001, the year the United Nations outlined its strategy for achieving the MDGs, assuming that progress should be measured against the moment MDGs were adopted.

3
# **1. Introduction**

It has been claimed that environmental risks are a constraint to sustainable economic growth and lasting poverty reduction, especially in dynamically growing countries. Vietnam has experienced an average annual GDP growth of about 5.5 percent since 1990 and reduced extreme poverty from around 60 percent in 1990 to 13.5 percent as of 2014 (World Bank Group, 2016).<sup>1</sup> Nevertheless, pockets of poverty still exist today: 91 percent of people in extreme poverty live in rural areas and belong to marginal groups, such as ethnic minorities, who have a poverty rate of about 58 percent (Kozel, 2014).

At the same time Vietnam is facing various environmental challenges. Land is increasingly degraded by human‐ induced factors (Vu et al., 2014a, Vu et al., 2014b). Although total tree cover has increased, certain areas suffer from high rates of natural forest loss and forest degradation (Pham et al., 2012). Satellite data suggest that air pollution is increasing to high levels (World Bank Group, 2016). At the same time weather variability and extreme events, such as floods and droughts, severely affect livelihoods (Arouri et al., 2015; Bui et al., 2014; Narloch, 2016; Thomas et al., 2010). All of these risks could be exacerbated by population growth, unmanaged development and climate change.

These interlinkages between poverty and environmental risks could be mutually‐reinforcing ‐ often referred to as the environment‐poverty nexus (Reardon and Vosti, 1995). Due to the lack of other opportunities, many of the poor live in high risk areas where they are more exposed to hazards and are more vulnerable to any negative impacts (Hallegatte et al., 2016). Many of them also overly depend on ecosystems and natural resources for income generation (as shown for Vietnam in Narloch, 2016) and to cope with shocks (Angelsen et al., 2014;
)|
|**% Fixed assets funded by other**||0.0299|
|||(0.0635)|
|**Additional controls**|Asper Eq (1)|Asper Eq (2)|
|**Country FE**|Yes|Yes|
|**Year FE**|Yes|Yes|
|**Observations**|9,126|9,112|
|**Number of countries**|104|104|

Note: This table reports the results of the estimation of Equation (1) and (2). The sample comprehends firms above the median value of value of real annual sales scaled by total number of employees. Under the column (OLS), the dependent variables are the innovation score and adoption score, as described in Table 1. Under the column (Logit), the dependent variables are the innovation dummy, the adoption dummy and invention, as described in Table 1. For logit regressions, we report the marginal effects at the means for the explanatory variables. *, **, and *** represent statistical significance at 10%, 5%, and 1% twotailed level, respectively. Robust standard errors in parentheses, clustered at strata level.

The degree of a country's financial development may also play a role in explaining the relationship between firm innovation and the sourcing of funding of fixed assets. In detail, the association between financing obtained through the formal financial system may be stronger in countries with more developed financial markets and institutions because of the variety of instruments, investors and ancillary services that may spur investment in innovation. Using the financial development index computed by the International Monetary Fund (IMF),<sup>8</sup> we split the sample into countries with low financial development (i.e., in the first quartile of the distribution of the IMF financial development index), and high financial

> 8 The explanation and data for
of intergenerational educational mobility (see the survey by Torche (2019)). The rst two columns in Table 2 report the estimates from the linear model, while the last two from the quadratic model. We report the estimated eects of Inpres schools on the parameters of interest (intercept, linear, and quadratic terms of the mobility models), and the full set of coecient estimates for the corresponding DiD models are reported in online appendix Table A.1.

The estimates from the linear model suggest that, for sons (superscript _s_ denoting sons), ˆ there is a positive eect on the intercept _β_ 4<sup>_s_= 1</sup><sup>_._59</sup> , and a negative impact on the slope � � ˆ (IGRC) _β_ 7<sup>_s_=</sup><sup>_−_0</sup><sup>_._13</sup> .<sup>35</sup> The evidence on the slope thus suggests that the Inpres schools � � weakened the impact of family background and improved the relative mobility of boys irrespective of a father's education level. The positive eect on the intercept suggests that the most disadvantaged children (fathers with no schooling) beneted in the form of higher expected years of schooling as a result of the Inpres schools. However, the estimated eects for daughters are numerically much smaller and are not signicant at the 10 percent level, suggesting that the expansion of the primary schools failed to aect the educational mobility of the girls in a signicant way. This absence of a signicant eect for girls is unexpected because a substantial literature suggests that availability of schools in a village is more important for girls.

Linearity is a maintained assumption in the estimates in columns (1) and (2) of Table 2, but a growing theoretical and empirical literature suggests that the intergenerational education mobility
the peak quarterly increase in the unemployment rate was considerably later in 2001:Q4. Second, the model also predicts _low_ levels of TTBs over the period 2004:Q2 through 2007:Q4; this compares well with the realized data on new TTBs.

On the other hand, the model cannot match the magnitude of the spike in realized US TTBs in 2001:Q2. These were almost entirely associated with one single policy decision, i.e., the US steel safeguard initiation in June 2001. However, the US steel safeguard had a number of unique properties, from the perspective of this modeling exercise. First, it was a single action covering hundreds of products. Furthermore, and despite the exclusions and exemptions which pierced the full nondiscriminatory nature of the policy (Bown, 2004), the import restriction still covered many trading partners, a number of which may not have been substantial suppliers of US steel import products. Finally, in the quarterly data, the singular timing of this policy action also ends up being recorded as quite different from a set of similar (in the aggregate) antidumping actions in 1991-92, for example. Because those many separate antidumping actions fell over a couple of different quarters (e.g., 1992:Q2, 1992:Q3) there was not as large a spike in any one quarter as was recorded during the 2001 recession.

# **5 Conclusion**

This paper uses quarterly data for the United States, European Union, and three other industrialized economies to estimate the impact of macroeconomic shocks on import protection over 1988:Q12010:Q4. Estimates from a data sample taken before the Great Recession exhibit evidence of three key relationships. First, there is strong evidence of a countercyclical relationship between domestic macroeconomic shocks – increases in domestic unemployment rates or reductions in domestic real GDP growth – and governments initiating new temporary trade barrier investigations over significantly more imported products per trading partner per quarter. Second, we find these economies used such bilateral import restrictions against trading partners that
**Figure 7:** Relative risk rates obtained from multinomial logit regressions: improved (above) and worsened (below)

<!-- Start of picture text --> (a) By classes (b) By quintiles<br>MRP # Poor MRP # Poor<br>MRP # Vulnerable MRP # Vulnerable<br>MRP # Lower-middle class MRP # Lower-middle qgp<br>MRP # Middle class MRP # Middle qgp<br>MRP # Upper-middle class MRP # Upper-middle qgp<br>MRP # Poor MRP # Poor<br>MRP # Vulnerable MRP # Vulnerable<br>MRP # Lower-middle class MRP # Lower-middle qgp<br>MRP # Middle class MRP # Middle qgp<br>MRP # Upper-middle class MRP # Upper-middle qgp<br>0 1 2 3 4 5 0 1 2 3 4<br>Relative risk rate Relative risk rate<br>Improved Improved<br>Worsened Worsened<br><!-- End of picture text --> _Source:_ Authors’ calculations based on Morocco’s household surveys.

As opposed to results for “Worsened”, for which most of the coefficients are not statistically significant, the results for “Improved” relative to “Not changed” are particularly insightful with respect to the relation between consumption polarization and household self-reported welfare. Keeping all the other variables constant, if polarization were to increase, the relative probability of declaring that a household’s welfare improved, rather than not changed, is  1  0.431  100  56.9% lower for the poor,  1  0.574  100  42.6% lower for the vulnerable, and  1  0.872  100  12.8% lower for households in the lower-middle class—albeit the 95 percent confidence interval of the corresponding relative risk rate overlaps with 1 (0.713—1.068); hence, this decrease in relative probability is not
East Asia and the Pacific|26|21|15|13|9|14|13|
|Europe and Central Asia|31|30|25|18|26|24|24|
|Latin America and the Caribbean|31|25|17|18|17|16|15|
|Middle East and North Africa|14|12|6|5|9|6|6|
|Other High-Income economies|60|28|19|0|18|19|19|
|South Asia|8|7|6|6|5|5|6|
|Sub-Saharan Africa|48|45|37|32|34|36|37|
|_World_|218|168|123|91|118|120|119|
|_World (incl. data older than 5 years_<br>_and adding in datafrom WDI)_|218|168|129|92|118|126|125|

Source: Authors’ compilation from the GMD, ASPIRE, and Findex databases. Notes: Income refers to having less than 1.5*$2.15 per household member, education refers to no adult having primary schooling, social protection refers to not receiving any social protection, and financial inclusion refers to not having a bank or mobile money account. Water refers to access to limited standard water, and access to electricity is as written. The coverage year for education, water and electricity is based on the filters of +- 5 years from 2019, and for social protection is based on the filter of +- 5years from 2017.

> 24 For China, we used the Household survey CHIP 2013 for dimensions of education and social protection.

22
70 percent of households. Cash is transferred to households earning less than JD 10,000 (US$14,000) a year at a rate of JD 70 (US$100) per person up to six members per household annually, provided that the oil price is above US$100 a barrel. To sharpen targeting, the government later tightened the eligibility criteria by adopting proxy means testing that took into account not only wage income but also consumption and asset indicators. In 2014, the government specified asset thresholds for cars, land, and real estate ownership. The government further developed the national unified registry database in the Income and Sales Tax Department to link it to other databases and rank families according to proxy‐means test scores (IMF 2014e).

The price of LPG sold in 12.5‐kg cylinders, intended for household use, had been fixed for years at JD 6.5 per cylinder, or US$733 per tonne (US$0.73 per kg), and then raised and fixed at JD 10 per cylinder (US$1,128 per tonne) between November 2012 and December 2014. During the same period, Saudi Aramco’s contract price for LPG rose above US$1,000 per tonne on several occasions, and exceeded the
Policy Research Working Paper 7646

# **Abstract**

There is wide variation in how consumption is measured in household surveys both across countries and over time. This variation may confound welfare comparisons in part because these alternative survey designs produce consumption estimates that are differentially influenced by contrasting types of survey response error. Although previous studies have documented the extent of net error in alternative survey designs, little is known about the relative influence of the different response errors that underpin a survey estimate. This study leverages a recent randomized food consumption survey experiment in Tanzania to shed light on the relative influence of these various error types. The observed deviation of measured household consumption from a benchmark is decomposed into item-specific consumption incidence and consumption value so as to investigate effects related to (a) the omission of any consumption and then (b) the error in value reporting conditional on positive consumption. The results show that various survey designs exhibit widely differing error decompositions, and hence a simple summary comparison of the total recorded consumption across surveys will obscure specific error patterns and inhibit the lessons for improved consumption survey design. In light of these findings, the relative performance of common survey designs is discussed, and design lessons are drawn to enhance the accuracy of item-specific consumption reporting and, consequently, the measures of total household food consumption.

This paper is a product of the Poverty and Inequality Team, Development Research Group. 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 jfriedman@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