rafmacalaba/datause-encoder-data huggingface dataset:
“ <mark>Measurement drives diagnosis and response. As global attention returns to food security, new opportunities emerge to improve its measurement...</mark> ”  Chris Barrett (2010), _Science_

# **1 INTRODUCTION**

The world is facing significant and interrelated challenges in the areas of food security, malnutrition, and chronic poverty. A large portion of the world’s population still lives below the poverty line, and despite rapid economic growth and a significant reduction in extreme economic poverty, hunger and malnutrition have remained stubbornly high in some parts of the world, particularly in South Asia and Sub-Saharan Africa (United Nations, 2012). Moreover, even in regions where food security improved significantly prior to 2005, food price shocks experienced in 2008 and 2011 reversed some of this progress, leading to increased poverty (Ivanic and Martin, 2008; Ivanic et al, 2011) and undernourishment (Tiwari and Zaman, 2010). From a policy perspective, these issues underscore the need for sustained efforts to address the vulnerabilities that the world’s poor face in meeting their basic food and nutritional needs.

Of particular concern is the extent to which children are affected by these shocks. Young children are known to be especially vulnerable to any shock that may weaken the household’s ability to secure food during times of economic distress. In addition, since body size at adulthood is strongly correlated with stature at age three, any growth faltering experienced in these early formative years may leave a permanent physiological as well as socio-economic scar. The latter is due to the fact that children’s nutritional status in early childhood has been found to be correlated with cognitive outcomes, productivity, earnings and the risk of cardio-vascular and obstructive lung diseases.<sup>1</sup> Two kinds of interventions are particularly emphasized to protect children’s nutritional status during times of economic distress. The first takes the form of social safety nets and is intended to provide immediate relief in the form of direct transfers – of cash or often also food – to households most likely to be affected by these shocks. The second takes a more medium- to long-term perspective and is geared towards building resilience to future shocks through better integration with national and international agricultural markets through commerce and trade, crop diversification, increased productivity through use of weather -resistant seed varieties, increased production of nutrient-dense food items etc. Even though it is now well understood that malnutrition is a multidimensional problem and requires coordinated action on several fronts, the goal of these interventions is to ensure that the causal pathway linking nutrition to household food security remains intact, and in particular, the quantity and quality of nutritional intake does not suffer.<sup>2</sup> This view is at the very foundation of the renewed emphasis, particularly in program activities in the agricultural sector, on sharpening their nutritional focus.

2
**1.56** -

-

**IV. Main aid Nos MOM Lkdw Papuluiwi.** v & **Wag O** **_wt_**

|Period|Grain|<br>120|CO;OA PRO<br>140|DUCER PRICE (1<br>160|987 CEDIS/KG)<br>180|<br>200|
|---|---|---|---|---|---|---|
|1990-94<br>1995-99<br>2000-04<br>2005-09<br>2010-14<br>2015-19<br>2020-24<br>2025-29<br>2030-34<br>2035-39|Maize<br>Maize<br>Maize<br>Maize<br>Maize<br>Maize<br>Rios<br>**Maize**<br>**Rice**<br>Maize<br>Rice<br>Maize<br>Maize<br>**Rice**|284.8<br>649.7<br>788.9<br>942.4<br>1110.5<br>1158.0<br>1491.7<br>1706.2<br>450.3<br>1938.4|534.7<br>649.7<br>788.9<br>942.4<br>1110.5<br>1295.2<br>1491.7<br>1706.2<br>771.3<br>2125.5|534.7<br>649.7<br>788.9<br>942.4<br>1110.5<br>1295.2<br>1491 7<br>1706.2<br>1316.8<br>2125.5|534.7<br>649 7<br>788.9<br>942.4<br>1110.5<br>1295.2<br>1491.7<br>83.5<br>1706.2<br>217.6<br>1393.7<br>2125.5|534.7<br>649.7<br>788.9<br>942.4<br>1110.5<br>1295.2<br>45.<br>1491.7<br>83.5<br>1706.2<br>217.6<br>1393.7<br>2125.5<br>354.5|

implied by this supply response are giver, In Table I.C.6 and these exhibit the same pattern as previous scenarios, elastic at low prices and inelastic at higher prices.

The simulated patterns of cocoa production over time for various buying prices under this scenario are In general quite similar to the stepped cycles of the population growth only scenario. However, In this sconarlo, the lowest buying price of 120. cedis per kilogram has cocoa production collapsing to qulte low levels as other crops are more attractive. That is, the growth In Income stimulates demand for foods, raising the prices of nontradable foods, and shift'ng resources away from cocoa production. In addition, the stimulus to food demand from Income growth boosts imports of food grains to levels that reach 1.5 to 2.5 million tons per year In the later time periods.

The simulated patterns of cocoa acreage adjustment under this scenarlo, shown In Flgure I.C.12, show the rough step function of the previous scenario at the hlgher prices. At the 120 cedis per klogram price, acreage collapses to under one mililon acres. At a price of 140 cedis per kilogram, acreage Just malntains its Initial level of silghtly over two millon acres. Thus, the price beiow which demand becomes elastic becomes 160 cedis per kilog-am under this scenario. The simulated levels of farm Income in the Income growth, constant wage scenario, shown In Fiqure I.C.1 3, follow the rough step function of
<!-- Start of picture text --> non-grain sugar & starch fuel ethanol projects for non-grain fuel ethanol and biodiesel(Wang,<br>(Wang, Zhao, & Zhang, et al., 2010) ; Zhao, & Zhang, et al., 2010);<br>· Lack of transparent access policy for biodiesel; · Permit more competitor in the processing and<br>retailing sectors(Li & Chan-Halbrendt,2009);<br>Lack of standard and regulations for sustainable · Set standard and regulations on sustainable<br>production of biofuels (i.e., what kinds of marginal land production of biofuels (Wang, Zhao, & Zhang, et al.,<br>is available for energy crops from the sustainable 2010);<br>perspectives ) (Wang, Zhao, & Zhang, et al., 2010) · Integrate the environmental and social performance<br>of biofuels with economic and non-economic<br>incentives;<br>Information and acceptance barriers<br>Lack of knowledge on environmental and social · Further improve Life cycle analysis methodology for<br>externality of biofuels (RGCREDS, 2008; Wang, Zhao, biofuels (Wang, Zhao, & Zhang, et al., 2010;<br>& Zhang, et al., 2010; Chang, et al.2012) IEA,2012; Chang, et al., 2012);<br>· Potential impact of biofuels production on the grain<br>security and agriculture development(Huang, et al.<br>2010, Fu, et al. 2011)<br>· Potential ecological environment problems caused by<br>large-scale cultivation of energy crops (EBSDEC,<br>2009)<br>Lack of resource assessment (i.e., quantity and · Further improvement of method on resource<br>distribution of marginal land in China for energy crops) assessment; Carrying out resource assessment,<br>(Wang, Zhao, & Zhang, et al., 2010) especially in resource rich provinces; (EBSDEC,<br>2009; Wang, Zhao, & Zhang, et al., 2010)<br><!-- End of picture text --> Each technology faces respectively the different barriers, but supply cost is one of the major barriers faced by all pathways, especially that of feedstock cost. Non-grain fuel ethanol attracts more concerns to address their economic barriers as policies suggested shown in table 12. Second-generation biofuels are projected as the most promising pathway in medium- and long-term. Several countries have preferential provisions that encourage the use of second-generation biofuels (e.g. specific policy target in the United States). Policy support for second-generation biofuels in China focused mainly on research and development (R&D), while there are almost no specific policies for deployment of second-generation biofuels in China. It is necessary to shift gradually from R&D to market deployment policies.

Non-economic barriers still exist in China, like administration. Most of existing policies related to fuel ethanol are aimed at grain based ethanol (i.e., corn or wheat). Without central government permission, new fuel ethanol companies have no access to the biofuels industry, no financial subsidies, tax exemptions and bank credits support, even no access to the distribution channel. Despite the existence of the entry regulation, there are still no transparence indicators or guidelines on what kind of starch and sugar energy crops should be designated.

Considering the uncertain impacts of large scale biofuels production on climate security, as 18
# Table 9: Households - Diff-in-Diff regressions

||(1)|(2)<br>|(3)|(4)|(5)|
|---|---|---|---|---|---|
||Urban<br>Planning Systems|Fiduciary<br>Responsability|Infrastructure<br>Management|Accountability<br>& Transparencey|Views on<br>Taxation and Fees|
|||**Panel A: Sim**|**ple diferences-**|**in-diferences**||
|ULGSP * Round 2 (DiD)|0.030|0.060|0.135|0.015|0.014|
||(0.091)|(0.092)|(0.121)|(0.179)|(0.107)|
||[-0.155, 0.218]|[-0.136, 0.252]|[-0.109, 0.370]|[-0.348, 0.385]|[-0.208, 0.231]|
|ULGSP LGA|0.043|-0.007|0.435***|0.075|0.349***|
||(0.086)|(0.080)|(0.131)|(0.128)|(0.102)|
||[-0.125, 0.209]|[-0.179, 0.151]|[0.168, 0.699]|[-0.203, 0.348]|[0.134, 0.552]|
|Survey Round 2|0.408***|0.136**|0.263***|-0.056|0.521***|
||(0.071)|(0.066)|(0.089)|(0.110)|(0.092)|
||[0.260, 0.556]|[-0.00201, 0.272]|[0.0868, 0.452]|[-0.306, 0.181]|[0.325, 0.716]|
|Observations|5468|3719|2896|976|4492|
|R-Squared|0.045|0.007|0.092|0.002|0.099|
|Mean Dep Var|-0.000|0.000|0.000|0.000|0.000|
|Number clusters (LGA)|40|40|40|40|40|
||**Pa**|**nel B: Diference**|**s-in-diference**|**s including contro**|**ls**|
|ULGSP * Round 2 (DiD)|0.038|0.043|0.098|0.013|-0.002|
||(0.092)|(0.087)|(0.121)|(0.180)|(0.104)|
||[-0.142, 0.228]|[-0.139, 0.226]|[-0.151, 0.350]|[-0.365, 0.379]|[-0.208, 0.210]|
|ULGSP LGA|0.036|-0.020|0.351***|0.039|0.283***|
||(0.082)|(0.080)|(0.127)|(0.138)|(0.101)|
||[-0.122, 0.200]|[-0.194, 0.150]|[0.0811, 0.618]|[-0.250, 0.318]|[0.0725, 0.491]|
|Survey Round 2|0.393***|0.097|0.247***|-0.090|0.508***|
||(0.073)|(0.064)|(0.087)|(0.111)|(0.089)|
||[0.240, 0.553]|[-0.0381, 0.236]|[0.0757, 0.426]|[-0.322, 0.138]|[0.324, 0.701]|
|Observations|5462|3717|2892|976|4487|
|R-Squared|0.079|0.047|0.164|0.035|0.135|
|Mean Dep Var|-0.000|-0.000|-0.000|0.000|0.001|
|Number clusters (LGA)|40|40|40|40|40|

_Note:_ This table reports regressions using each of the described indices as dependent variable. Non-reported comparators in the second panel include welfare index, household size, age, gender, marital status and education levels. Standard errors clustered at the LGA level are reported in parentheses (* p<0.1, ** p<0.05, *** p <0.01), while 95% confidence-intervals constructed using wild-bootstrapping are reported in brackets.

51
# **On the Relevance of Freedom and Entitlement in Development: New Empirical Evidence (1975-2007)**

_Jean-Pierre Chauffour_<sup>_1_</sup> World Bank JEL Classifications: O1, K19, D63, C21, C23 Keywords: Economic growth, economic freedom, entitlements, institutions, human rights

> 1 Lead Economist, International Trade Department, World Bank. The paper draws on my book, _<u>The Power of Freedom: Uniting Human Rights and Development</u>_ (Cato Institute, 2009) and was prepared for the International Symposium on the MDGs and Human Rights held at Harvard University on March 22-23, 2010. I am grateful to Marlya Maliszewska for excellent research assistance and to Milan Brahmbhatt, Bernard Hoekman, Susanna Lundstrom and Maurice Schiff for useful comments. The paper benefited from comments from Emmanuel Teitelbaum and other participants at the Conference on Human Rights, Development, and Economic Growth – Metrics, New Ways of Thinking, and New Strategies organized by George Washington University on April 7-8, 2011. The views expressed in this paper are solely my own and should not be attributed to the World Bank, its Executive Directors or the countries they represent. I can be contacted at jchauffour@worldbank.org.
**Table S15. Probability of care that meets minimum quality standards (%): by country**

||(1)<br>|(2)<br>Probability of<br>|(3)<br>Care Readiness<br>|(4)<br>|
|---|---|---|---|---|
|_Condition_|As observed|Assume<br>available<br>drugs|Assume<br>provider<br>presence|No. of<br>facilities|
|Kenya|45.3|51.2|60.2|1,646|
||(43.0-47.6)|(49.0-53.5)|(57.7-62.7)||
|Madagascar|1.9|2.0|1.9|459|
||(-0.3-4.0)|(-0.2-4.1)|(-0.3-4.0)||
|Mozambique|16.4|19.6|17.2|204|
||(11.5-21.4)|(14.3-24.9)|(12.0-22.4)||
|Niger|4.3|8.2|5.8|256|
||(2.0-6.6)|(4.4-11.9)|(2.8-8.8)||
|Nigeria|3.8|6.4|4.3|2,358|
||(2.8-4.8)|(5.2-7.6)|(3.2-5.4)||
|Sierra Leone|25.5|40.6|31.0|399|
||(21.6-29.5)|(36.4-44.8)|(26.7-35.4)||
|Tanzania|25.4|39.1|27.4|180|
||(20.1-30.7)|(32.4-45.9)|(21.8-33.1)||
|Togo|0.0|0.0|0.0|390|
|Uganda|-<br>1.0|-<br>4.7|-<br>1.3|544|
||(-0.1-2.1)|(2.2-7.2)|(0.1-2.6)||

**Note** : Column (1) reports the estimated probability of care readiness that meets minimum quality standards for child, neonatal & maternity care (diarrhea, pneumonia, post-partum hemorrhage, and neonatal asphyxia). Column 2 reports the estimated probability of care readiness that meets minimum quality standards, assuming essential drug(s) (oral rehydration salts or rehydration therapy for diarrhea; antibiotics for pneumonia; and oxytocin for postpartum hemorrhage) for treating the conditions are available. No essential drugs data were collected for neonatal asphyxia. Column 3 reports the estimated probability of care readiness that meets minimum quality standards, assuming no more than 5% absenteeism. All individual country statistics calculated using country-specific sampling weights. 95% confidence intervals in parenthesis. Number of facilities reported in column 4.

61
# **Optimal Allocation of Natural Resource Surpluses in a Dynamic Macroeconomic Framework:** A DSGE Analysis with Evidence from Uganda

Albert Zeufack<sup>_∗_</sup> Alexandre Kopoin<sup>_†_</sup> Jean-Pascal Nganou<sup>_‡_</sup> Fulbert Tchana Tchana<sup>_§_</sup> Laurent Kemoe<sup>_¶_</sup> December 8, 2016 _JEL Classification_ : E22, F43, O41, Q32 _Keywords:_ Fiscal policy; public investment; resource-rich developing countries; macroeconomic volatility; optimal resource allocation.

> _∗_ Chief Economist, Africa Region, The World Bank, email: azeufack@worldbank.org.

> _†_ Economics Department, OECD and Laval University, email: alexandre.kopoin@oecd.org.

> _‡_ Senior Country Economist, The World Bank, email: jnganou@worldbank.org.

> _§_ Senior Economist, The World Bank, email: ftchanatchana@worldbank.org.

> _¶_ Department of Economics and CIREQ, University of Montreal, email: laurent.kemoe@umontreal.ca. We are grateful to Kevin Moran, Jean-Pierre Par ́e, Gilles Belanger, Fall Falilou, Juste Some, seminar participants at CSAE Conference 2015: Economic Development in Africa and anonymous referees for helpful comments.
TabWe I Effects on World Price of Sustained Expansions from 1985 Onwards

|Year|Simulated<br>World Price|--------<br>8.3% increa|-----------<br>se in exports<sup>*</sup><br> <br>|Cangein<br>32.6% incre<br>|World Pr e<br>ase ip exports*<br>|--<br>96.1 % incre<br>|ase<sup>'n exports*</sup><br>|
|---|---|---|---|---|---|---|---|
||USc/lb|%|Elasticity of<br>Export Deman<br>|%<br>d<br>|Elasticity of<br>Export Deman<br>|%<br>d<br>|Elasticilty of<br>Exp)ort Demano<br>|
|1 985|7.3|-4.4|-3.1|- 16.4<br>|-3.3<br>|-40.2<br>|-40<br>|
|1 986|6.1|-5.7|-2.5|-20.6<br>|-2.7<br>|-47.9<br>|-3 3<br>|
|1 987|8.3|-6.2|- ?.7<br>|-22.6<br>|- 1.8<br>|-52.7<br>|-2 2<br>|
|1 988|9.0|-5.5|- 1.8<br>|-21 .1<br>|- 1.9<br>|-52 0<br>|-2 2<br>|
|1989|1 4.5|-5.5|- 1.6|-20.7|- 1.7<br>|-54 0<br>|- 1.8<br>|
|1 990|1 4.1|-3.5|-2.7|- 16.3|-2.3<br>|-48 2<br>|-2 3<br>|
|1 99 1|1 1 8|-2.5|-3.7<br>|- 12.7<br>|-3.0<br>|-42.3<br>|-2 6<br>|
|1 992|1 5.2|-2.6|-3. 1<br>|- 1 1.2<br>|-2.9<br>|-38 2<br>|-2 5<br>|
|1993|26.6|-2.6|-3.0|-10.4<br>|-3.3<br>|-36 0<br>|-2 5<br>|
|1 994|22.4|- 1.8|-4.6|-6.7|-4.9<br>|-24 6<br>|-4 0<br>|
|1 995|1 3.7|-0.7|-1 1.6|-2.2<br>|- 1i1.2<br>|- 10 8<br>|-9 0<br>|
|1996|11.9|-0.8|-9.4|-4.2|-7.1<br>|-13.7<br>|-65<br>|
|1997|13 0|- 1.5|-4.9|-7.7<br>|-3.8<br>|-23 1<br>|-3.8<br>|
|1 998|1 4.0|-2.1|-3.7<br>|-9.3<br>|-3.3<br>|-26.4<br>|-3 5<br>|
|1999|13 6|-2.2|-3.4|-8.8<br>|-3.4<br>|-27.0<br>|-3 3<br>|
|2000|12.9|-2.3|-3.3|-9.0|-3.4<br>|-26 0<br>|-3 4<br>|
|2001|18.6|-2.1|-3.1|-8.1|-3.2<br>|-25.8<br>|-3 0<br>|
|2002|20.6|-1.4|-4.9|-6.3<br>|-4.4<br>|-22 8<br>|-3 6<br>|
|2003|1 7.3|- 1.7|-4.0|-4.6<br>|-6.0<br>|-1 68<br>|- 4 9<br>|
|2004|15.4|-0.6|- 10.7|-3.2|-8.2|- 1 3.6|-58|
|Avereae|14.3|-2.4|-3.5|-9.8|-3.3|-30 1|-3?|

**>:** Baseline average of 60 stochastic<sup>simulations</sup> in 1984 dollar terms. Average increase across all<sup>simulations</sup> and all years.
Table 1: Venezuelan Net Population Displaced Abroad Over the Years

|2010|2015|2019|
|---|---|---|
|Worldwide<br>556,641|695,551|4,326,330|
|South America<br>62,240|86,964|3,239,730|
|North America (US+Canada)<br>196,910|273,418|371,919|
|Europe (Portugal, Spain, Italy)<br>203,117|224,328|309,170|
|Central America & Mexico<br>21,260|33,065|166,974|
|Carribbean<br>19,629|21,74|119,333|
|Others<br>53,485|56,702|119,204|
|South America|||
|2010|2015|2020|
|Colombia<br>43,511|48,714|1,717,352|
|Peru<br>3,504|4,129|1,043,460|
|Chile<br>8,095|54,787|475,702|
|Ecuador<br>6,120|8,901|415,835|
|Brazil<br>2,844|3,425|261,441|
|Argentina<br>1,236|1,240|217,562|

Source: Author’s calculation from UN Data This paper attempts to fill this gap by investigating how integrated the Venezuelan refugees and migrants are in the education, formal labor market and social protection sectors of Brazil<sup>4</sup> and how di↵erent economic and social factors accelerate or hinder the process of integration. By integration, this paper refers to the definition advocated by OECD (2011) that defines integration as a two-way process of adaptation by migrants and host societies that includes the rights, obligations and access to di↵erent kinds of services and the labor market. Another contribution of this paper lies in the fact that unlike Colombia, Peru and Ecuador, on which previous studies have focused, Brazil has universal access to education, healthcare and social protection irrespective of documentation status and prohibits any kind of discrimination at work (Selee and Bolter, 2020) and consequently it serves as a case study to see whether di↵erent legal constraints can lead to di↵erential observed outcomes.<sup>5</sup> This paper refers to this di↵erent legal framework in Brazil as little or minimum legal constraints in line with Selee and Bolter (2020) and Mazza (2020), however in reality, it still might be challenging for Venezuelans to integrate.

Measuring integration calls for a benchmark against which outcomes can be assessed and this

> universities.

> 4Access to health service is an important dimension of integration that we do not focus on this paper due to unavailability of data.

> 5Olivieri et al. (2020), Graham et al. (2020), Uscategui and Andrea (2019), Selee and Bolter (2020) and Mazza (2020) report that Venezuelans face legal restrictions, di↵erential access to education, health, labor martket and safety net programs and hostility in Colombia, Peru and Ecuador.

3
9 preparing and teaching lessons addressing a specific goal of their choosing, while others observe and record the lesson, and subsequently provide feedback and make suggestions for improvement (Darling-Hammond et al., 2010). Singapore’s Teachers Network learning circles – in which between four and ten teachers and a facilitator meet for eight two-hour sessions over a period of four to twelve months, to collaboratively identify and solve common problems using discussions and action research – similarly encourage teachers to be reflective practitioners (DarlingHammond et al., 2010).

Limited high-quality experimental or quasi-experimental evidence makes it difficult to draw detailed conclusions about what works within teacher training even in rich countries. However, from a combination of the more rigorous quantitative and qualitative studies above, there is suggestive evidence that in-service teacher PD programs in high-income countries have been most effective at improving student learning where they have been embedded in the curriculum; prescribed a specific method, with detailed instructions on implementation; included significant and sustained in-person follow-up support for teachers; and involved teachers in a colearning model.

# **3. Method**

To understand which characteristics of PD programs are associated with student test score gains, and to analyze the degree to which these effective characteristics are incorporated into atscale PD programs in practice, we first developed a standardized instrument to characterize inservice teacher training. Second, we applied this instrument to already evaluated PD programs to understand which PD characteristics are associated with student learning gains. Third, we applied the survey instrument to a sample of at-scale PD programs to see how these programs line up with what evidence suggests works in teacher training. The information we present thus comes from
traceability throughout the chain up to the level of overseas producers forms parts of many private standards, including the GlobalGAP.

As a result, exporting adequate quality products requires producers to invest in production infrastructure, revise their practices through sta¤ training and implement traceability systems. A signi...cant body of literature provides evidence that these compliance costs are non trivial and may be su¢ cient to disrupt ...rms trade relationships. Maskus et al., (2005) use ...rm-level data from 16 developing countries in the World Bank Technical Barriers to Trade (TBT) Survey Database. Their ...ndings indicate that standards do increase short-run production costs by requiring additional inputs of labor and capital. They show that a one percent increase in investment to meet compliance costs in importing countries raises variable production costs by between 0.06 and 0.13 percent in the exporting country. Additionally, they ...nd that the ...xed costs of compliance are signi...cant and amount approximately $425,000 per ...rm, or about 4.7 percent of value added on average. Other attempts to quantify the compliance costs include the recent study by UNCTAD (2005). The costs of compliance with SPS for tropical fruits in three sub-Saharan African countries–including United Republic of Tanzania, Mozambique and Guinea–are estimated using the GlobalGAP protocol as a case study<sup>2</sup> . Appendix 8:B reports results for Tanzania. These ...ndings illustrate the importance of both recurring operating and ...xed investment costs, suggesting that compliance is both a costly and lengthy process. While these costs may be born publicly, in practise, the lack of technical and administrative capacities in developing countries implies that the cost burden fall onto individual ...rms. Their ability to secure su¢ cient liquidity to insure ongoing production as well as to make the necessary investments is essential to their pro...tably remaining on the market. In this manner, the relative under-development of ...nancial systems in sub-Saharan African countries may constrain ...rms access to capital and subsequent export survival. The next two sections present our choice of empirical strategy and the data.

# 3 Empirical Strategy

Our hypothesis is that ...nancial development di¤erentially a¤ects the survival of exports across products based on their sensitivity to SPS regulations. A measure of sanitary risk at the product level (Jaud et al., 2009a) serves as a proxy for ...nancing needs of agri-food products.

This di¤erential e¤ect calls for a di¤erence-in-di¤erence approach initially proposed by Rajan and Zingales (1998). Their seminal paper emphasizes the bene...cial implications of ...nancial development for industries dependent on external ...nance. To capture 2The GlobalGAP was designed to accommodate the requirements set out by international standards as well as EU regulations. For these reasons, it is a good proxy to estimate the necessary costs of complying with standards and providing safe –non rejected –products.

6