rafmacalaba/datause-encoder-data huggingface dataset:
(2004) have shown that product variety and quality are important in explaining trade between nations. Feenstra et al. (1999) show that increased variety of exports in a sector increases total factor productivity in most manufacturing sectors in Taiwan (China) and Korea, and they have some evidence that increased input variety also increases total factor productivity. In business services, because of the high cost of using distant suppliers, the close availability of a diverse set of business services may be even more important for growth than in goods. The evidence for this was cited in the introduction section.

Beginning with the path-breaking work of Coe and Helpman (1995), a rich literature now exists that has empirically investigated the transmission of knowledge through the purchase of imported intermediate goods and through foreign direct investment. We summarize this literature in appendix H. In summary, this literature shows that the purchase of intermediate inputs and FDI from industrialized countries is an important mechanism for the transmission of R&D and productivity growth in developing countries. For small developing countries, trading with large technologically advanced countries is crucial for TFP growth. But for products in which developing countries have a comparative advantage, developing country trade may be important for spillovers.

In our model, the parameter that reflects the ability of a region to increase total factor productivity through the transmission of new technologies is the elasticity of varieties with respect to the price. Schiff _et al_ ., (2002, table 1) have shown that for R&D intensive sectors, trade with industrialized countries contributes significantly to total factor productivity in developing countries, but trade with developing countries does not. Averaging over the industries in Schiff _et al_ .,( 2002, table 3) yields that trade with industrialized countries in R&D intensive products is about eight times more valuable for developing country TFP increases. On the other hand, for sectors that are low in R&D intensity, their results suggest that for technology diffusion trade with developing countries can be as important as trade with industrialized countries.

Based on these considerations, we first classify the increasing returns to scale sectors of our model into low, medium and high technology sectors. Due to lack of data for Armenia, the classification is defined by the share of R&D expenditures in total sales, based on U.S. data. For low R&D intensive sectors, we assume that the elasticity of firms with respect to price is the same for the CIS region as for the EU, but the elasticity is only one-third of Rest of the World 20
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number of other regulatory and system attributes to enable the estimation of equations to predict the numbers of staff required.

The data were of generally high quality although there were some question marks for individual country responses. More importantly, the definition of “professional” in numbers of professional staff may well have been rather different (and less demanding) for many DTEs relative to the North American and EU countries in the sample.

The DPS data confirmed that there were fixed staff costs for countries establishing an electricity regulator. This raises serious problems for small countries like Grenada or Namibia. They also, however, showed that developing country regulators had noticeably _higher_ staff numbers per million customers per sector regulated - a mean number of 59 staff per million for developing countries as opposed to a mean of 15 per million for developed countries. _The difference was that developing countries had a much lower number of connected customers relative to population_ . Plotting average cost curves, developing countries were concentrated in the relatively steep initial portion of the curve, with many above the fitted line<sup>31</sup> .

The data above indicate some of the difficulties for developing countries in establishing an effective regulatory capability. This was demonstrated more directly in the econometric equations used to explain staff numbers and professional staff numbers. The estimates from the regressions suggested that, even for small countries with limited electricity systems, the minimum number of regulatory staff required was around 30-35, including around 15-20 professional staff. Predictions using the relevant equations for three small, developing countries not in the DPS sample – Guatemala, Sri Lanka and Zambia - yielded the following numbers for staff requirements:

||Total Staff|Professional Staff|
|---|---|---|
|Guatemala|58|33|
|Sri Lanka|48|26|
|Zambia|57|45|

Clearly, many developing countries do have staff (and professional staff) numbers at or above the DPS predictions. Latin American regulators generally seemed to be well-staffed and to have more staff (and professional staff) than the DPS equations predicted. That was the case for several of the regulators in smaller and poorer Latin American countries (eg Bolivia, Ecuador and Peru). However, many DTEs – particularly smaller African and Caribbean countries - have significantly fewer staff than predicted (eg Kenya, Grenada). But, even here, the results were not always toward significant under-prediction viz. Uganda, a major African electricity reformer,

> 31 See DPS (2002), pp 19-25.

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Policy Research Working Paper 11013

# **Abstract**

This paper uses a rich set of geo-coded administrative and remotely sensed data on more than 1 million agricultural land transactions in Ukraine to explore how informality, size, and recent land reforms affect land prices. Three main findings are highlighted. First, absence of registered rights generates large negative externalities, the size of which plausibly exceeds the cost of registering all land. By contrast, informality of lease contracts is a choice that may enable owners to evade regulatory obstacles that prevent them from renegotiating contracts to obtain more favorable terms. Second, while land market liberalization generated significant indirect benefits, gains are unevenly distributed. Furthermore, competition in sales markets remains limited, pointing to scope for measures—including reducing the transaction costs of selling land and accessing mortgage finance, improving publicity of pending land sales, and use of electronic auctions—to enhance the reforms’ impact on efficiency and equity. Third, size at the parcel, field, and farm levels is associated with higher per hectare prices, pointing to scope for market-based land consolidation and growth of medium-size farms to increase land values and productivity. Achieving this potential will require measures to limit speculative land acquisition and exercise of market power by making local land markets more competitive and using market-based land valuation as a basis for taxing land on a recurrent basis and any capital gains due to land appreciation.

This paper is a product of the Development Research Group, Development Economics. 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 kdeininger@worldbank.org and dali1@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
# **Figure 1: Total Number of Climate and Environmental related Natural Disasters Over Time**

This figure shows the total number of disaster episodes around the world. For a disaggregated presentation across disaster groups, see Appendix, Figure 7 <!-- Start of picture text --> iv) a call for international assistance<br>iii) an official declaration of a state of emergency<br>400 ii) 100 or more people affected<br>i) 10 or more people reported killed<br>300<br>200<br>100<br>0<br>1960 1970 1980 1990 2000 2010 2020<br><!-- End of picture text --> countries covered, and hence decided against it. We focus on the instance of disaster instead of the precise damage figures for two reasons: 1) EM-DAT damage figures are missing for most developing countries and hence using damage figures will introduce a rich-country bias3 hard to correct for, in addition to significantly trimming the sample, and 2) anecdotal evidence and on-the-ground experiences tend to suggest that these damage figures are not very precise and accurate.

This section focuses on key stylized facts related to climate and environmental related natural disasters. We consider eight types of natural disasters related to climate change or environmental risks: wild fire, volcanic activity, earthquake, storm, landslide, drought, flood and extreme temperature. While a specific type of event can occur many times in a country each year, an episode is defined if the event occurs at least once in a country in a year. Therefore, there are typically more occurrences than episodes. The remainder of this paper focuses on the impacts of episodes.

Climate and environmental related natural disasters have increased in frequency between 1960 and 2020. Figure 1 presents the number of disaster episodes categorized by severity during the last 60 years. Between the periods 1960-79 and 2000-2020, the number of disaster episodes has almost tripled. Disaster episodes associated with an official declaration of a state of emergency (level iii) or a call for international assistance (level iv) account for a small proportion of the total number of disasters in a given year, with the former still occurring every year and the latter rarely seen in most years. These observations are generally true for all eight types of disasters, with the share of severe disasters (levels iii and iv) relatively higher in some years for wildfire and droughts. See Appendix, Figure 6 for the relative share of episodes across regions and figure 7 for a visual breakdown of disaster episodes by disaster group.

> 3For instance, damage amount data is available for 46 percent of high income countries but only 18 percent of low income countries.

6
and The availability of data for 1990 also allows us to study the impact of diaspora on the change in the selection ratio (which is broadly equal to the selection ratio of new migrants). The two estimated speci...cations are then obtained by substituting ln(Sij) by its change between 1990 and 2000, �ln(Sij).

# 4.3 Relative Concentration

We also explore the relative concentration of diasporas across education levels. In particular, we ask whether diasporas tend to lead to more concentration of unskilled rather than skilled migrants at a given destination. We construct our destinationspeci...c relative concentration measure as the following: where indices s and u refer to skilled and unskilled migrants. A nice property of this bilateral measure is that its sum across destination countries j boils down to the di¤erence between Her...ndhal indices for skilled and unskilled migrants.

Once again, we consider regression models with and without destination dummies and consider regression on levels (relative concentration Cij<sup>s�C</sup> ij<sup>uobservedin2000)</sup> and on change between 1990 and 2000. The models for the levels are: and The speci...cations relative to the changes are obtained by substituting Cij<sup>s�C</sup> ij<sup>u</sup> relative to 2000 by �(Cij<sup>s�C</sup> ij<sup>u) where �refers to the change between 1990 and 2000.</sup> The latter speci...cation is particularly demanding since the dependent measures "a di¤erence in di¤erences" of concentration rates.

# 4.4 Econometric Issues

The estimation of models (10-15) entails several econometric challenges that might lead the estimation of those models by OLS to generate inconsistent estimates. There are two basic reasons. The ...rst one is related to the occurrence of zero or unde...ned values for the dependent variables in a large portion of the observations. The second one is the potential correlation of ln(Mij) with �ij due to the presence of an unobservable component a¤ecting the size of the diasporas and the characteristics of new migrants. We now discuss how we address these issues.

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In 2014, the State Council promoted the permanent settlement of 100 million migrants in urban areas and unification of the agricultural and nonagricultural _Hukou_ classifications (State Council, 2014a). A 2019 Urbanization Plan requires cities with fewer than 5 million residents to lift or relax urban residency restrictions, potentially granting migrants access to the same rights and services as existing urban _Hukou_ holders (National Development and Reform Commission (NDRC), 2019). Because these reforms excluded most migrant workers in large cities, they are not viewed to be meaningful for most migrants (Chan, 2019). For instance, regulations for obtaining a local Beijing _Hukou_ still favor the highly educated and those serving the capital’s political functions over less-skilled rural migrant workers (Liu and Shi 2020). A new dataset (1978-2016) on prefecture-level migration regulations reveals variations in migrant treatment across prefectures. In particular, prefectures with high export potential have the friendliest policies toward migrants (Tian, 2022).

In sum, the _Hukou_ system has been modified to accommodate internal migration and urbanization, however in the large cities, the primary destination of rural-to-urban migrants, it continues to sustain labor market segmentation. Even after the 2008 Labor Contract Law and the 2011 Social Insurance Law aimed to bring migrants into urban social insurance programs, participation remained low (Giles et al., 2021). At the same time, local regulations toward migrants exhibit substantial variation across prefectures, with policy responding to labor market demands, particularly in regions with high export potential.

# **2.2. The Land Tenure System**

China’s land tenure system creates disincentives for farmers to fully participate in the off-farm labor market. The state owns land in urban areas, while rural collectives own agricultural land and homestead land in suburban and rural areas.<sup>5</sup> Individuals and for-profit organizations have land _use_ rights for fixed periods, and rural households have 30-year land use rights under contractual arrangements with their village.<sup>6</sup> These individual land use rights are distinct from and independent of land ownership by collectives and the state, this legal framework has been described as a “dual land tenure system” (Khantachavana et al., 2013; World Bank, 2014).

> 5Land ownership is stipulated in Article 8 of the Constitution of the People’s Republic of China, amended in 1998, and in Article 10 of the Constitution, amended in 2004.

> 6Under the original Household Responsibility System (HRS), rural households were granted 15-year land use rights in the early 1980s.  When the original 15-year leases expired in the late 1990s, the national government extended the term of farmers’ use rights for an additional 30 years, and codified terms of 30-year land use rights under the 1998 Land Administration Law (Davis and Chen, 1998).

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In addition, one may be concerned about the robustness of the above results, especially, the positive coefficient of domestic market accessibility ( _TC1_ ). Two different definitions of “market” are examined. First, the market is defined by cities with more than 100,000 population ( _TC1a_ ). Nineteen locations are identified in our data. Second, the market is defined by the regional or zonal capitals. This comprises 59 cities, some of which are relatively small in terms of population ( _TC1b_ ).

The results remain broadly unchanged ( **Table 7** ). Under the spatial autocorrelation framework, the coefficients of local market, either _TC1a_ or _TC1b_ , are still positive but statistically not significant. As discussed above, one possible reason is that our identification strategy may be weak to measure the possible impact of local market connectivity on agricultural production. Another possibility is that the result may reflect the fact that agriculture production takes place in rural areas: Agriculture production is higher where it is far from major cities.

**<u>Table 7. Robustness check with different definitions of “domestic market”</u>**

||Spatial regr|ession||Spatial regr|ession||
|---|---|---|---|---|---|---|
||Coef.|Std.Err.||Coef.|Std.Err.||
|Δln_LAG_|0.224|(0.043)|***|0.226|(0.043)|***|
|Δln_LNON_|0.134|(0.044)|***|0.132|(0.044)|***|
|Δln_R_|0.403|(0.003)|***|0.403|(0.003)|***|
|Δln_I_|0.070|(0.007)|***|0.070|(0.007)|***|
|Δln_F_|0.010|(0.001)|***|0.010|(0.001)|***|
|Δln_TC1a_|0.345|(0.231)|||||
|Δln_TC1b_||||0.227|(0.181)||
|Δln_TC2_|-0.097|(0.041)|**|-0.097|(0.041)|**|
|constant|-0.350|(0.057)|***|-0.346|(0.057)|***|
|Obs|4624|||4624|||
|F statistic|||||||
|Wald2|18413.3|||18478.4|||
|R-squared|||||||
|Spatial parameters:|||||||
|_λ_|0.080|(0.010)|***|0.079|(0.010)|***|
|_ρ_|0.303|(0.004)|***|0.303|(0.004)|***|

Note: The dependent variable is Δln _Y_ . Robust standard errors are shown in parentheses. *, ** and *** indicate statistical significance at the 10, 5 and 1 percent level, respectively.
3D PRINTING AND TRADE 8

# **3. Differences-in-Differences**

In this section, we study the impact of 3D printing on international trade flows using a differences-in-differences method. We ask the data four main related questions: what the impact of the new technology is on hearing aids’ (i) average exports; (ii) comparative advantage; (iii) exports of countries at different level of developments; and (iv) imports.

In the simplest case, 3D printing would reduce trade if countries shifted from importing hearing aids to printing them. However, it could also affect comparative advantage, leading to a change in trade patterns, but no end to trade. In a standard Heckscher-Ohlin framework, the introduction of 3D printing technology would reduce the labor intensity of production. As a result, exports would shift to more capital abundant countries. The overall reshuffling of exports would also depend on the presence of economies of scale. Finally, the new technology reduced production costs and increased product quality, suggesting there should be greater demand, more production, and potentially more trade.

We begin by identifying the effect of 3D printing on trade by comparing hearing-aid exports before and after 2007 – the year production technology shifted – to exports of other products. The underlying assumption is that, controlling for other determinants of trade, trade in hearing aids would have moved in parallel to other products in the absence of the 3D printing technology. Thus, any divergence in hearing aids trade after 2007 is attributable to 3D printing.

To formally investigate the relationship between 3D printing and trade, we estimate the following equation: where XiktP is country i’s log of exports of HS 6-digit product k within category product P in year t.<sup>10</sup> Ikt(Hearing Aid 2007) is an indicator variable which takes value 1 for HS code 902140 “hearing aid” from year 2007 onward – the year in which the technology became widely used in the production of hearing aids (see Section 2). γik and δit are country-product and country-year fixed effects, respectively. Country-product dummies capture the effect of time-invariant characteristics that determine the level of exports, including secular productivity and endowment differences that can determine the specialization trade patterns. While country-year fixed effects account for country specific shocks common to all products, including country-specific macroeconomic conditions.

> 10 We use product level bilateral trade data from WITS (UN Comtrade) reported at the 6-digit level in the HS 1988/92 classification for the period 1995-2016 .  As common in the literature, we drop countries with population less than 5 million. Additionally, we keep only countries for which the World Bank provides information on the income level (see Table 9 or <u>https://datahelpdesk.worldbank.org/knowledgebase/articles/378834-how-does-the-world-bank-classifycountries).  The available data cover 117 countries and 330 products that are either classified as high-tech</u> (see Table 5) or in HS chapter 90.
and the exponential of the negative of entropy, which measures the diversity of a node's connections. Connectivity can thus be summarized as the product of remoteness and diversification.<sup>13</sup> In the context of air transport, the first factor has a lot to do with geography, while the second is likely also influenced by policies that tend to establish more connections with the rest of the world through a more "open sky".

Table 1 provides a comparison of the _Air Connectivity Index_ (ACI; equation 7) with the other measures of connectivity discussed in Appendix 3, in terms of the criteria set out at the beginning of this section. As can be seen, the ACI is the only measure that responds to all five desirable criteria for a measure of connectivity.

**Table 1: Comparison of the ACI with alternative measures of connectivity.**

||Realistic|Intensive|Normalized|Local|Global|
|---|---|---|---|---|---|
|UNCTAD (2007)|Y|N|N|N|N|
|Pearce (2007)|Y|N|N|Y|N|
|Kullback-Leibler distance|N|Y|Y|Y|Y|
|Clustering Coefficient|N|Y|Y|Y|N|
|PageRank or Eigenvector Centrality|partial|Y|N|Y|Y|
|Closeness centrality|partial|Y|Y|Y|Y|
|ACI|Y|Y|Y|Y|Y|

# **4.3 A Simple Example**

To see how our measure of connectivity works in practice, we take a simple example that is of some relevance to the air transport setting. We assume a network consisting of two layers: an inner layer of fully connected hubs, and an outer layer of spokes attached to the hubs (Figure 5). All links have the

> 13 We note in passing that the decomposition proposed here retains data on observations where no actual flow is observed, due to the presence of summation operators prior to taking logarithms.

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