rafmacalaba/datause-encoder-data huggingface dataset:
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live and where they go. It is noteworthy that transport infrastructure forms a network. Thus, transport connectivity should be measured in a continuous manner and at a more granular level.

7. To overcome these data challenges, the paper proposes to construct a spatial connectivity dataset using detailed shipment data. Our spatial data allows for estimating transport costs or travel time at each individual road level. Dorosh et al. (2009) use similar geospatial data to identify the impact of market accessibility on crop production in Africa. Their cross-sectional approach remains subject to the potential risk of omitted variable bias and uncontrolled infrastructure endogeneity. This paper takes advantage of stop-by-stop freight shipment data collected over the period 2010-2020.<sup>1</sup> Detailed historical changes in transport connectivity in the Caucasus and Central Asia region are measured. Then, they are regressed on firm location data.

8. The remaining sections are organized as follows: Section II provides a brief regional and country context and elaborates on how our transport measurements are constructed for the sample region. Section III discusses our empirical strategy and summary statistics. Section IV presents the main estimation results. Section V discusses robustness and heterogeneity of the results. Then, Section VI concludes.

# **II. Regional and Country Contexts and Transport Connectivity Measurements**

9. Recent global crises, such as the Coronavirus Disease 2019 (COVID-19) and the war in Ukraine, have reminded us of the importance of maintaining efficient and reliable transport and logistics networks to ensure economic growth.<sup>2</sup> Because of the stagnation and faster-thanexpected recovery in merchandise trade and global outputs, the world shipping capacity remains constrained by shortages in logistical equipment, containers, service operators, such as truck drivers and port operators, and cargo vessels (UNCTAD 2021). According to the Drewry database, the average global maritime freight rate reached over US$10,000 per 40-foot container

> 1 See ADB (2020) for more details. We would like to express our special thanks to the Central Asia Regional Economic Cooperation (CAREC) member countries and the Asian Development Bank (ADB) Corridor Performance Measurement and Monitoring (CPMM) team for sharing relevant raw shipping data. 2 The following analysis examines the period from 2010 to 2020. The impact of the COVID crisis may not be reflected sufficiently in our dataset.
silent on how such skills affect country participation in GVCs especially in manufacturing GVCs. The lack of empirical evidence on this area hampers the design of policies which aim at improving country participation in GVCs and ‘social upgrading’ (Grundke et al., 2017b).

Recently, researchers such as Grundke et al. (2017b) attempted to estimate the effect of skills on country participation in GVCs. However, there is no consensus on the direction of causality. This is because higher skill endowment is expected to contribute to the participation, competitiveness and positioning of countries in the global value chains (Kowalski et al., 2015). At the same time, countries are likely to gain substantial skill-benefits from higher engagement in GVCs (Del Prete et al. 2016). Del Prete et al. (2016) provide suggestive evidence that skill is one of the fundamental determinants of country participation in GVCs for North African countries, using recently released multi-regional Input-Output tables from UNCTAD-Eora. However, they pointed out that the ability to benefit and retain the benefits from GVC participation depends on country specific characteristics such as the level of human capital development.

While existing studies agree on the importance of skills in country GVC participation, they seldomly specify which skills matter for which types of GVC participation. To fill this gap in the literature, Grundke et al. (2017b) investigate the extent to which different skills and their distributions relate to global value chains in order to identify the specific skills that affect participation in GVCs. They find that cognitive skills, ICT skills, management and communication skills, and readiness to learn new skills have significant positive effects on integration into GVCs. However, this relationship is stronger for cognitive skills than for the other skill indicators. Furthermore, Grundke et al. (2017a) explore how the skill composition of a country's workforce (both types of skills and their distribution) shapes specialization in specific industries as well as their competitiveness and integration into GVCs. They find that industry competitiveness and positioning in GVCs depend on bundles of skills at the worker level, rather than on workers endowed with only one type of skills. They also find that workers’ observed heterogeneity in skills' mix (i.e. their bundles of skills) and country-wide dispersion of these skills are fundamental determinants of countries’ specialization in specific industries and the extent to which these industries integrate into global markets. For example, two countries characterized by similar average levels of "literacy skills" may end up specializing in completely different industries and 5
Policy Research Working Paper 7138

# **Abstract**

This paper uses farm panel data from China to examine the dynamics of land transactions, machine investments, and the demand for machine services. Recently, China’s agriculture has experienced a large expansion of machine rentals and machine services provided by specialized agents, which has contributed to mechanization of agricultural production. The empirical results show that an increase in nonagricultural wage rates leads to expansion of self-cultivated land size. A rise in the proportion of nonagricultural income or the migration rate also increases the size of self-cultivated land.

Interestingly, however, relatively educated farm households decrease the size of self-cultivated land, which suggests that relatively less educated farmers tend to specialize in farming. The demand for machine services has also increased if agricultural wage and migration rate increased over time, especially among relatively large farms. The results on crop income support the complementarity between rented-in land and machine services (demanded), which implies that scale economies are arising in Chinese agriculture with mechanization and active land rental markets.

This paper is a product of the Agriculture and Rural Development 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 fyamauchi@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
19 acquire a dwelling of given attributes in urban areas over-compensates for the higheL prices of those attributes.

This study has offered and implemented a tractable empirical method for estimating spatial cost-of-living differentials which can deal with these problems. Hedonic rent indices are used as the prices for housing in an AIDS demand model, the calibration of which permits parameters of the consumer's cost-of-utility function to be retrieved. The paper has applied the method to a large household level data set for Java. The results suggest that conventional housing rent and price comparisons do lead to a substantial over-estimation of the true cost-of-living in cities. And this is more pronounced at low incomes, since we find that the marginal cost of utility is larger (relative to expenditures) in urban areas, implying that the relative cost of urban living increases with income. In a neighbourhood of the poverty line, our results suggest that, allowing solely for the difference in price vectors, an urban-rural cost-of-living differential of about 10 percent is closer to the truth than the values (as high as 66 percent) that have been used in past work for Indonesia.
Our second key question is whether government-owned banks help in relaxing credit constraints during recessions. While there is evidence that lending by government-owned banks is less procyclical than lending by private banks (see, among others, Micco and Panizza, 2006, and Panizza, 2022), previous research could not establish whether countercyclical lending by government-owned banks has an effect on firm outcomes and whether lending countercyclicality particularly benefits credit constrained firms. This is important because credit constrained firms are likely to suffer the most from credit contractions during recessions. Our bank-firm matched dataset allows us to study this specific question. Note that access to credit in good and bad times will change for firms that are always completely excluded from the financial markets. However, all the firms in our sample do have a banking relationship and have borrowed at some point in time.

_What type of firms borrow from state-owned banks?_ To assess whether government-owned banks target credit constrained firms or firms that generate positive externalities, we use the three indicators described above to estimate the following model: The dependent variable is a firm characteristic based on one of the indexes described in the previous section (presence of credit constraints, innovation, green activities) for firm i, located in country c, in year t; GOBb(i)t is a dummy variable that takes value one if bank b used by firm i in year t is government-owned, Xb(i)t is a matrix of bank-level controls (size, proxied by the log of total assets, and profitability, proxied by return on assets), Wi(c)t is a matrix of firm-level controls (log size, log age, a dummy for state-owned firms, and a dummy for female-owned firms), and αct is a set of country-year fixed effects that control for all possible country-year specific factors. We also estimate models in which the dependent variable takes value 1 if the firm invested in year t. The idea is that there could be positive externalities associated with increasing investment. We estimate Equation 1 (and all the models described below) using the survey weights reported in the World Bank Enterprise Survey rescaled to add up to one for the firms included in the regressions.

While Equation 1 cannot tell us if the possible relationship between firms and government owned banks is driven by demand (i.e., firms with specific characteristics prefer to borrow from government-owned banks) or supply considerations (i.e., government-owned banks seek firms with certain characteristics), this is not an issue for us. If firms with certain characteristics prefer government owned banks, it must be the case that these banks offer them better conditions (in terms of quantity or cost of credit) which are specific to these 10
future, high-resolution DTMs based on technologies such as LIDAR might enable such an approach even at the country-level, but this is beyond the scope of this work.

# <mark>4.2.</mark> Flood exposure of agriculture and aquaculture production

The exposure of agricultural production to flooding is estimated based on the land-use maps described in section 3.1. Specifically, a distinction is made between areas where there is farming of rice, orchards and other crops. As the resolution of the datasets differs, the flood maps are scaled up to match the detailed resolution of the land use data. This can be conceptualized by dividing a square into four new squares that occupy the same area. For each agricultural land use type and each flood return period, the amount of flooded agricultural area per province is extracted using a spatial overlay. This is done separately for coastal flooding and for riverine flooding. Agricultural area is considered to be flooded if it is affected by flooding to a depth of at least 25cm, a threshold chosen as most plants cannot withstand flooding above this height. Finally, the results of flood-exposed agricultural area are corrected to account for existing flood protection infrastructure in each province, as described in section 4.1.

Figure 4.1 and Figure 4.2 give an overview over the exposure of crop and rice production to flooding of three different return periods while accounting for protection infrastructure.

**Figure 4.1: Agricultural crop production is particularly exposed in the Red river and Mekong delta, especially for coastal flooding**

_a) Coastal flood risk: exposure of all agricultural land (sum of rice, crops and orchards)_ <!-- Start of picture text --> 300<br>250<br>200<br>150<br>100<br>50<br>0<br>Return period: 1-in-25 1-in-100 1-in-500<br>97%<br>67%<br>88%<br>89% 43%<br>99% 99%<br>24% 100%<br>97% 13% 34%<br>71%<br>81%<br>(hectares, thousands)<br>Exposed agriculture land 33% 22% 90%<br>21%<br>9%<br>5% 1% 1% 1% 1% 2% 0% 0% 12%<br>Quang Ninh Hai Phong City Thai Binh Nam Dinh Ninh Binh Thanh Hoa Nghe An Ha Tinh Quang Binh Quang Tri Thua Thien-Hue Da Nang City Quang Nam Quang Ngai Binh Dinh Phu Yen Khanh Hoa Ninh Thuan Binh Thuan Ba Ria-Vung Tau Ho Chi Minh City Tien Giang Ben Tre Tra Vinh Soc Trang Bac Lieu Ca Mau Kien Giang<br><!-- End of picture text -->

- _b) Riverine flood risk: exposure of all agricultural land (sum of rice, crops and orchards)_

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social interaction are important, in large cities associational forms are sturdier than everyday forms of engagement, especially when confronted with attempts by politicians to polarize people on ethnic lines.

# **Quadrant 4 - Coping: Poorly Functioning State, Abundant Cross-Cutting Ties**

Societies with higher levels of cross-cutting ties rather than deep social cleavages and ineffective or co-opted states are characterized by the substitution of the formal system by informal systems. If the state is not totalitarian or coercive, societies may not disintegrate into widespread crime, violence or war, but large segments of society are left to their own devices to cope in the best ways they can.

Richard Rose (1995) uses the term "hour-glass society" to describe such societies, like Russia during the transition. There is a rich social life at the base, consisting of strong informal networks relying on trust between friends, relatives and other face-to-face groups and which may include friends of friends. At the top of the hour glass, there is rich political and social life, as elites compete for power, wealth and prestige. There is co-operation within and between elites and formal institutions as the elites use the resources of the state for their own betterment. The narrow mid-point of the hour-glass insulates individuals from the influence of the state, and citizens can be described as "negatively integrated" from the demands of potentially oppressive state. The state on the other hand tolerates small-scale "rogue" organizations as long as they do not interfere with the affairs of the state.

Using data from the New Russia Barometer, a nation-wide survey, Rose documents that only one in eight reported that they earned enough from their official jobs to meet their basic needs. The majority get by because in addition to the official economy, they rely on a multiplicity of unofficial economies such as growing food, exchanging help and services with friends, having a second job or depending on tips and bribes. There is a vast disconnect between the rich social mechanisms and exchanges at the bottom and local formal institutions. Three-quarters of the people also said that they never participated in local level formal institutions. The same proportion said that most people cannot be trusted and that one had to be careful in dealing with people. The level of distrust in political parties, parliament, police, court and civil servants ranged from 71 percent to 83 percent. When asked if they expected fair treatment, 70 percent responded 31
# 5. Sample and Experiment Design

<mark>The 2012 World Bank Group‐supported Economic Revitalization of KP and FATA (ERKF) project provided a unique setting to compare individuals who received a cash grant to rebuild or establish businesses in the conflict‐ affected area with individuals who received both a grant and the 5‐ week PM+E training intervention. This allowed for the testing of the hypothesis that financial assistance coupled with the psychosocial training would be more effective than just receiving cash grants in reducing depression and anxiety, the most common manifestations of psychosocial distress.</mark>

# 5.1 Sample Size Calculations

<mark>The unit of randomization in the study was individual entrepreneurs, with an equal number of entrepreneurs randomized into the intervention and control groups. The sample size was estimated using a recent study that measured changes in the occurrence of depressive symptoms as measured by the PHQ‐9 (as a proxy for the PHQ‐ADS, which has not been applied in similar contexts). The study utilized a sample of primary care (clinical) participants in the same area of Pakistan that showed a similar PM+ intervention had an effect size of 0.725 with a PHQ‐9 total score as the outcome. An effect size which is one‐third of the precedent effect size was assumed because the current sample was not derived from a clinically‐referred population. Factoring this in, a 20 percent reduction (roughly, one‐third of 0.725) in the occurrence of psychological distress</mark> was considered meaningful.

<mark>Power calculations suggested a minimum sample size of 84 participants per arm (power = 0.90; α = .05, 2‐sided). To account for a 25 percent attrition at the 3‐month follow‐up, a total of 235 participants were included and randomized into intervention (n=118) and control (n=117) arms (Saraf, Rahman, Hamdani, Jamison, and others, 2018).</mark>

# 5.2 Sample, Recruitment, and Data

<mark>A sample of 235 SME entrepreneurs was drawn from among beneficiaries of the ERKF cash grants program. All participants received a cash grant of 2 million Pakistani Rupees (PKR) (approximately US$14,300) from ERKF for rehabilitation of their businesses. Participants were invited to join the training program from different locations of KPK, and were between 21 to 80 years of age. The majority (95 percent) of the entrepreneurs in the sample were male, which is representative of</mark> the ERKF beneficiary pool.

<mark>Data were collected on psychological indicators of study participants across three rounds. All data were conducted via telephonic interviews. The baseline survey was conducted prior to the start of the intervention, the first midline survey immediately after delivery of the intervention (at the 5‐week mark), and a follow‐up midline survey 3 months after the intervention via telephonic interviews. An endline survey is scheduled to be completed 18 months after the intervention.</mark>

# 5.3 Randomization

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