rafmacalaba/data-use-mentions-extended huggingface dataset:
Policy Research Working Paper 5903

# **Abstract**

This paper studies the volatility of commodity prices on the basis of a large dataset of monthly prices observed in international trade data from the United States over the period 2002 to 2011. The conventional wisdom in academia and policy circles is that primary commodity prices are more volatile than those of manufactured products, although most of the existing evidence does not actually attempt to measure the volatility of prices of individual goods or commodities. The literature tends to focus on trends in the evolution and volatility of ratios of price indexes composed of multiple commodities and products. This approach can be misleading. Indeed, the evidence presented in this paper suggests that on average prices of individual primary commodities are less volatile than those of individual manufactured goods. However, the challenges of managing terms of trade volatility in developing countries with concentrated export baskets remain.

This paper is a product of the International Trade Department, Poverty Reduction and Economic Management Network. 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 author may be contacted at dlederman@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
firms with access to a credit line bank with a foreign state bank. On average, foreign banks perform better than state-owned banks, based on our bank health index.

Finally, the legal origins are determined using the data from La Porta et al. (2008). Our sample is almost evenly split between French or German legal country origin. According to La Porta et al. (2008), both French and German legal origins follow civil-law traditions and have their roots in Roman law, but the latter accommodates greater judicial law-making. Countries following common-law or UK legal traditions are barely present in our sample.

**Table 1. Summary statistics**

||**N**|**Mean**|**SD**|**Min**|**Max**|
|---|---|---|---|---|---|
|**New Products/Services Introduced Over Last 3 Yrs –**<br>**_(innovation diffusion or new to thefirm)_**|28239|0.19|0.39|0|1|
|**Products/Services introduced are also new for the**<br>**establishment's main market****_(radical innovation)_**|8002|0.62|0.49|0|1|
|**R&D expenses during the past FY**|28228|0.05|0.21|0|1|
|**Line of credit**|27858|0.28|0.45|0|1|
|**State bank**|26718|0.09|0.29|0|1|
|**Foreign bank**|26053|0.12|0.32|0|1|
|**Foreign state bank**|
of product‐lines subject to TTBs by 25% during the crisis, most of this is the result of developing economies that combined to increase their stock of product coverage by 40%. Perhaps surprisingly, high‐income economies increased their stock of products affected by TTBs by only 5% during the crisis.

Furthermore, these changes during the global economic crisis are consistent with pre‐crisis trends in the data on TTB use. Developing countries have been increasing their use of TTBs prior to the crisis at such a rate that it is difficult to claim empirically that the 2008‐2009 crisis _caused_ developing economies to increase their stock of TTBs above what the simple time trend would predict even in the absence of a major global recession. On the other hand, the U.S. and EU have reduced the stock of imported products they subject to TTBs by up to 50% over the last fifteen years, which is consistent with the crisis data, indicating a muted response to political calls for new TTBs.

Also significant are the trends in the data from the perspective of the exporting economies. By 2009, China had roughly four times as many products subject to foreign‐imposed TTBs as the second most‐targeted economies. Furthermore, the share of China’s exports to other _developing_ economies is subject to much more foreign‐imposed TTBs than its share of exports to developed economies, and it is also growing at a faster rate. My evidence confirms that this particular feature is not unique to China but is shared by a number of other major developing economy exporters, thus deepening the concern that such discriminatory trade barriers are increasingly a “South‐South” phenomenon.

Finally, I conclude by commenting on how the lack of a substantial increase in new import protection resulting from the 2008‐2009 crisis beyond that predicted from pre‐crisis data raises important questions for research. If the world trading system does ultimately escape the 2008‐2009 crisis relatively unscathed with respect to new and extraordinary protectionist initiatives, an open and
cashiers in a grocery store with 60 employees. When collecting the five data points under the _Parenthood_ indicator, the research applies additional assumptions, such as that mothers and fathers have worked long enough to accrue maternity, paternity, and parental benefits.<sup>5</sup> In each data collection cycle, specific time frames are set, and only legislation entered into force in each time frame is measured. Only codified laws (including codified customary laws) are considered in data collection. WBL data were collected from primary legal sources and confirmed by local experts through the administration of standardized questionnaires. Historical data on laws and regulations before 2009 and going back to 1970 were collected through desk research of the primary legal sources and consulted with secondary sources where the primary ones could not be located.<sup>6</sup> We follow the WBL methodology in our analysis, and the total number of leave days available to a mother is calculated as the combination of maternity leave, parental leave days reserved for the mother and any additional days that are not specifically reserved for the use of either parent.<sup>7</sup> Fathers’ leave is the sum of paternity leave days plus any days of parental leave specifically allocated to the father. In our analysis, only paid leave is counted, and all leave days are calculated in calendar days. Continuing with the example of Germany, according to data for 2021, women in Germany are entitled to 98 days of maternity leave,<sup>8</sup> while there is no provision in place granting paternity leave specifically (fathers’ leave is only covered under parental leave policy). Thus, according to our method of counting leave days, total leave days for mothers is 458—of 98 maternity leave days, 60 parental leave days reserved for mothers, and 300 unallocated parental leave days. Total leave days for fathers is 60 days, comprised solely of parental leave days reserved for fathers.

> 5 The complete list of assumptions
|0.3077|0.8483 **|0.5640|1.0715 **|0.8264 **|1.0522 **|
|of trade (lagged)|(2.540)|(0.8025)|(2.077)|(1.417)|(2.558)|(2.019)|(2.493)|
|Change in output at|1.3480 **|0.2334|0.0690|0.8140|0.6825|-0.0152|0.6180|
|constant prices (lagged)|(2.437)|(0.380)|(0.106)|(1.230)|(0.969)|(-0.023)|(0.855)|
|Independent|-0.0186|0.0390|0.0217|-0.0048|0.0511**|0.0142|-0.0250**|
|term|(-0.629)|(1.591)|(0.806)|(-0.156)|(3.306)|(0.502)|(-0.740)|
|Adjusted R<sup>2</sup>|0.030|0.026|0.019|0.032|0.027|0.019|0.025|
|F test|8.17|7.07|4.42|6.68|4.59|3.51|3.70|
|Number of<br>observations|686|686|518|686|518|518|518|

Note: Data on average labor costs per worker are from the _Banque de Donnees Economiques et Financieres,_ which is composed of about one thousand medium and large firms. There is one
food prices. However, unlike the case described here, subjective assessments of food security and more traditional metrics are aligned in Headey (2012), where higher food prices are associated with worse subjective assessments of food security in the data and larger income growth is associated with better subjective assessments. The overall result is driven by the large income growth outweighing any negative impact of price increases; and the results are dependent on the inclusion of China and India, where price controls limited the increases in food prices and income growth was substantial.

> 5The problem of changing scales is not only a problem of subjective welfare questions. For example, the Reduced Coping Strategy Index (rCSI) is based on a number of questions about whether households engaged in particular coping strategies, and the frequency they used such a strategy if one was used. Some questions have individual-specific scales, such as whether households relied on less expensive foods; and other questions have standardized scales, such as whether households borrowed money to purchase food. However, during the conflict in the Republic of Yemen, both types of questions have been affected and the interpretation of the questions has likely changed relative to less tumultuous settings. For example, there might not be less expensive food available given poorly functioning food markets and supply chains, or being able to borrow money might be interpreted as a positive development because it indicates that lending markets work. Because of these difficulties in interpretation, these questions in particular have diverged from other food security measures (e.g., WFP 2019; Tandon and Vishwanath 2020; Tandon and Vishwanath 2021).

5
combine a large number of observations from different sources (e.g. satellites, weather stations, ships, aircraft) to produce a model of the global climate system or a particular atmospheric phenomenon. Reanalyses are assimilation models applied retrospectively over a given time period, to incorporate improvements in algorithms, data processing, and new data sets to support analysis of climate over the long-term. Outputs are inferred or predicted based on the system state and understanding of interactions between model variables. Outputs are differentiated at higher temporal resolution (sub-daily), as well as vertical/pressure levels, but typically lower spatial resolution than other weather data sets. We use two reanalysis data sets for both rainfall and temperature in this analysis: The European Centre for Medium-Range Weather Forecasts ERA5, gridded at 0 _._ 28<sup>_◦_</sup> , and the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA-2), on an irregular grid of 0 _._ 625<sup>_◦_</sup> _×_ 0 _._ 5<sup>_◦_</sup> (Hennermann and Berrisford, 2020; Bosilovich et al., 2016). The two sources have many inputs in common, although differ in processing routines and models. Papers which use ERA5 include Arslan et al. (2015), Asfaw and Maggio (2018), Kalkuhl and Wenz (2020), Sedova and Kalkuhl (2020), and Jagnani et al. (2021). Those which use MERRA-2 include Chen et al. (2017), Chen et al. (2018), and Letta et al. (2018).

# **2.1.3 Interpolated Gauge Data**

Last, we consider data products produced primarily from gauge data, using only spatial interpolation techniques to produce a continuous surface from observed measurements. The NOAA Climate Prediction Center (CPC) Unified Gauge-Based Analysis of Daily Precipitation and Temperature 9
net to include the whole set of outcomes covered in the literature: output micro and macro, labor market inequality and poverty, trade, human capital, population, environment, and land Value. Hundreds of papers and several literature reviews have been published and their focus has evolved over time. The first generation of research was mostly analyzing growth and productivity effects, based on a production function framework and using public capital data in a panel cross-section framework.<sup>1</sup> More recently, with the increasing availability of more granular information, including geospatial data, and the computing power to process very large databases, the focus has shifted to studies analyzing a wide array of outcomes, specific sectors, and implementing robust micro-econometric identification strategies.<sup>2</sup> We built a database of over a thousand estimates from 221 papers reporting infrastructure elasticities or semi-elasticities that can readily be converted into comparable elasticities. The papers included are the result of a systematic search through literature reviews and publication databases and were produced between 1983 and 2023.

We then analyze this data, starting with a visual examination through funnel plots, and distribution plots of test statistics following Brodeur et al. (2023). We then implement several econometric methods. We start by providing basic FAT-PET-PEESE type estimates (Stanley and Doucouliagos, 2012). FAT estimates and Caliper tests allow us to characterize potential publication bias and p-hacking. To provide estimates of specific “true” underlying effects of infrastructure, we report PEESE estimates. We then analyze in more details the heterogeneity in the sample, by introducing a large list of moderators related to both study design, and infrastructure sector and context characteristics. We report results based on several selection methods of moderators, including rigorous penalization for the LASSO, LASSO with 10-fold cross-validation for tuning parameter selection, and several Bayesian Model Averaging methods. We report results by sectors, as well as sectoroutcomes.<sup>3</sup>

> 1See Straub (2011) for a critical review, and Bom
Policy Research Working Paper 9604

# **Abstract**

To assess the impact of COVID-19 on firms, the World Bank and the International Finance Corporation conducted Business Pulse Surveys in several countries, including six in the South Asia region. Analysis focusing on the South Asia region suggests that, first, firms in the South Asia region have suffered disproportionately more from the economic brunt of the pandemic. Second, even within the region, COVID-19 did not affect all firms equally. Although exporters remain resilient by some metrics, firms that are smaller, female-led firms and those in vulnerable sectors suffered higher rates of closure. Third, while digital technologies have taken the center stage post-pandemic, the South Asia region lags in the adoption of these technologies. Finally, policy support for firms is key to building back better and resilient recovery, yet only a small share of firms can access public support. To be effective, firm support programs ought to be carefully customized and target firms based on the dominant channel through which COVID-19 affects them rather than their external attributes.

This paper is a product of the Finance, Competitiveness and Innovation 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 authors may be contacted at agrover1@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
United States declared bankruptcy, representing a 40% increase in filings from 2008 (American Bankruptcy Institute, 2010<sup>ix</sup> ).

The World Bank’s Financial Crisis Survey shows that in the EU, the use of bankruptcy procedures was less frequent than the use of state aid and debt restructuring. On average, 8.3 percent of European firms applied for state aid in the previous 12 months (as of June – July 2009), whereas, only 2 percent of all surveyed companies filed for bankruptcy. When considering only the subsample of firms with overdue payments, the proportion of firms that filed for bankruptcy increased to almost 6 percent, with the highest percent in Hungary (9.9%) (Correa and Iootty, 2010).

In light of widespread financial distress, many researchers have expressed concern that the costs of direct intervention of governments, such as giving assistance to individual companies, comes at a significant fiscal obligation to taxpayers. In addition, it prevents meaningful restructuring, encourages the private sector to expect similar assistance, gives incentive for imprudent risk-taking incentives, and paves the way for more frequent and costlier crises in the future (Caprio et al., 2008; Demirguc-Kunt and Serven, 2009; Demirguc-Kunt et al. 2008).

Encouraging bankruptcy reform could also be effective to encourage new entrepreneurship during a financial crisis. Policymakers drew an important lesson from the 1997 East Asia Financial Crisis in which several countries began reconsidering their corporate bankruptcy laws when existing bankruptcy systems did not allow the corporate sector to rehabilitate during long term economic recession (Armour and Deakin, 2001). When illiquidity spread across the region, South Korea, Malaysia, and Thailand were forced to modify their laws to favor the rehabilitation of distressed firms, as an alternative to liquidations (Carruthers and 14
# Ethnic Germans from Eastern Europe and Former Soviet Union to Germany after 1987

Ethnic Germans arriving in Germany with the lifting of emigration restrictions in central and eastern Europe and the Former Soviet Union (FSU) after 1987 did not face legal barriers on the labor market, as they were granted German citizenship upon arrival. Glitz (2012) exploits an exogeneous placement policy by the government which did not take labor market needs or skill composition into account. Looking at annual effects in the period between 1996 and 2001, the author finds a positive and significant short-run displacement effect but no conclusive effect on relative wages between OLS and IV results. The lack of short-term wage effects in the IV results might be explained by Germany’s strong union coverage at the time.

# Repatriates and escapees from Algeria to France

In the aftermath of Algerian independence in 1962, up to 900,000 people fled to France including 750,000 French nationals living in Algeria, about 100,000 naturalized Jews and several thousand pro-French Algerians who fought against the independentists. The French and Algerian caseloads were different in size but also in education level with the Algerians having the quasi totality of adults with less than primary education and the French having only about a quarter with this level of education. Both groups mostly settled in the Southern municipalities of France along the Mediterrean coast. A number of measures facilitated the integration of French repatriates into the labor market, including special benefits for up to a year to support the job search, a lump sum towards housing, and priority for certain jobs. Nevertheless, they had higher unemployment rates than natives in 1968 (Hunt 1992).

Using the 1962 and 1968 French censuses, Hunt (1992) studied this case focusing on French nationals and found a positive and significant small effect on the average locals’ unemployment rate and a negative and weakly significant effect on salaries at the national level, but does not differentiate between skill groups. Borjas and Monras included this caseload in their 2017 study distinguishing between French repatriates and Algerian emigrants.
34 The empirical specification of the intensification packages studied in the regression equations cannot exclude that additional factors also matter, such as the associated use of improved seeds, water control or soil fertility. These effects are controlled for to the extent that the instruments are able to isolate these practices from the ones studied (agrochemicals, mechanization). There are no obvious reasons to believe that they do not, but it cannot be fully excluded. Given the crosssectional nature of the data, and despite the inclusion of a broad set of controls including farmers’ attitudes (risk, information) to reflect farmer heterogeneity as much as possible, and the use of instruments, caution remains warranted in interpreting the coefficients as causal. Analysis using panel data or randomized controlled trials complemented with more complete information on the adopted packages and input quantities would be needed to establish this more firmly.

To conclude, the findings support the general notion that agricultural intensification can be profitable and that helping farmers intensify their production through the adoption of modern agricultural technologies such as tractors and chemical inputs, among others, contributes to increasing the returns to their labor, enhances specialization and commercialization, raises household income, and helps productively release agricultural labor for other crops and off-farm activities. It points to alleviation of the barriers to accessing these modern technologies as good policy entry points for supporting agricultural development and rural transformation.

The findings also underscore the importance of looking at returns to labor (instead of returns to land). Labor productivity is the more relevant metric in instigating structural transformation, despite the somewhat misguided focus of ministries and agricultural development agencies as well as the literature on yields (Cock et al., 2022). While this partly follows from the challenges related to measuring labor input in agriculture (Sagesaka et al., 2021), the focus of policy makers and the profession on yields also reflects the sectorial (focused on aggregate food production) as opposed
of avoiding “wasting” part of the data available in separate surveys, like LSMS and DHS. Sections 3.3 and 3.4.1 list solutions for the construction of hybrid multidimensional indices. They may thus help improve cross-regions well-being comparisons as well as a region’s well-being trend. The paper should study how to apply this kind of solutions in practice and quantify their impact on well-being comparisons.

39