rafmacalaba/datause-encoder-data huggingface dataset:
16 and the reduced form is: (14) (w-l)Av= **gi** _(n, y, X, p*, v, 1, k, !S!, SK,_ **_7C)_** Since X is predetermined with respect to the wage distortion, equation (13) can be estimated using ordinary least squares.

We estimate equations (12)-(14) using cross sectional data for 90 developing countries.<sup>1 3</sup> For a measure of trade distortion, **T,** we started by using the work of Dollar (1992) who estimates a measure of an economy's openness to trade for a large number of counties. This index-which we shall refer to from here on as DOLLAR-rises as the level of protection increases. Since this index is available only for 1990, our analysis using DOLLAR is limited to cross sectional work for that year.

However, DOLLAR, like most other measures of openness, does have some shortcomings. Pritchett (1991) shows that alternative objective measures of openness produce very different country rankings, and argues that the probability of deriving a single straightforward measure that produces a "correct" ranking of countries is very low. 14 Obviously, we do not attempt to find such a measure, but we experiment with using alternatives to DOLLAR to check the robustness of our conclusions. Three alternatives were used: the mean frequency of non-tariff barriers on manufacturing goods _(MNTB),_ the mean of total import charges on manufacturing goods (TARIFF), and the black market premium (BMP).

> **13** Since some data is missing for some countries the actual number of observations varies from one regression to the other depending on the availability of the variables included in the regression.

> **14** For further analysis of this question see Leamer (1988) or Harrisson (1991).
**<u>Table 6: Changes in prices and use of outputs and inputs as well as farm profitability, 2021–23</u>**

||<br>**2021**|<br>**2022**|<br>**2023**|<br>**Δ21-22**|**Δ21-23**|
|---|---|---|---|---|---|
|**Panel A: Output and input**<br>**prices**||||||
|_Output prices (US$/t)_||||||
|Winter wheat|240|137|129|-0.43|-0.46|
|Winter rapeseed|675|360|302|-0.47|-0.55|
|Spring barley|214|120|100|-0.44|-0.53|
|Corn|224|132|123|-0.41|-0.45|
|Sunflower|657|348|303|-0.47|-0.54|
|Soybean|602|336|381|-0.44|-0.37|
|_Input prices_||||||
|Seed (EU variety)|403|480|432|0.19|0.07|
|Fertilizer (ammonium nitrate)|383|615|410|0.61|0.07|
|Fertilizer (urea)|490|734|524|0.50|0.07|
|Pesticide|8.7|10.2|9.4|0.18|0.09|
|Plowing (1ha)|19.7|21.1|19.7|0.07|0.00|
|Harvesting (1ha)|38.7|41.0|38.3|0.06|-0.01|
|<br>Grain transport (t/30 km)|4.0|5.9|4.5|0.48|0.13|
|**Panel B: Farm-level data**||||||
|_Overall_||||||
|Area cultivated (ha)|216.8|215.1|226.5|-0.01|0.04|
|<br>Rapeseed yield (t/ha)|2.71|2.55|2.68|-0.06|-0.01|
|Maize yield (t/ha)|7.05|5.58|6.72|-0.21|-0.05|
|Sunflower yield (t/ha)|2.36|1.86|2.23|-0.21|-0.06|
|<br>Soybeans yield (t/ha)|2.45|2.05|2.42|-0.16|-0.01|
|<br>Wheat yield (t/ha)|4.25|3.45|4.03|-0.19|-0.05|
|<br>Barley yield (t/ha)|3.69|3.09|3.59|-0.16|-0.03|
|<br>Any sales|0.78|0.68|0.77|-0.13|-0.01|
|<br>Share of output sold|0.82|0.60|0.62|-0.27|-0.24|
|Revenue per ha|1,088|714|615|-0.34|-0.44|
|<br>Total input use per ha|<br>305|385|197|0.26|-0.36|
|<br>Profit per ha (US$)|778|313|418|-0.60|-0.46|
|<br>Number of farms|1,206|1,206|1,206|||
|_Farms <= 120 ha_||||||
|Area cultivated (ha)|54.4|58.2|57.2|0.07|0.05|
|Any sales|0.73|0.62|0.70|-0.16|-0.04|
|<br>Share of output sold|0.84|0.63|0.63|-0.25|-0.25|
|<br>Revenue per ha|1,034|690|584|-0.33|-0.43|
|<br>Total input use per ha|<br>275|358|196|0.30|-0.29|
|<br>Profit per ha (US$)|753|316|390|-0.58|-0.48|
|<br>Number of farms|817|817|750|||
|_Farms >120 ha_||||||
|Area cultivated (ha)|527.5|531.6|495.1|0.01|-0.06|
|<br>Any sales|0.87|0.80|0.87|-0.08|0.00|
|<br>Share of output sold|0.80|0.55|0.60|-0.31|-0.25|
|<br>Revenue per ha|1,215|773|662|-0.36|-0.46|
|<br>Total input use per ha|<br>377|453|198|0.20|-0.48|
|Profit per ha (US$)|839|306|463|-0.64|-0.45|
|Numberof farms|389|389|456|||

_Source:_ UCAB price data for panel A and household survey panel data for panel B, as described in the text. _Note:_ Prices in panel A are in US$ and exclude value-added tax. Output prices are at the elevator in central Ukraine. Profit is the value of output net of purchased inputs, that is, it includes remuneration for fixed factors and family labor. The six main crops are wheat, barley, rapeseed, soybean, maize, and sunflower. ha = hectares; km = kilometer; t = ton.

23
44

# Table 2

# Capital Flowa Under the Baker Plan: 1986-88 ($ millions)

||Banks(a)|Public Se|ctor|||Total|
|---|---|---|---|---|---|---|
|||Multilate|ral<br>Bilateral|<br>IMF,|<br>Total||
|Argentina|2,607|1,680|716|844|3,240|<br>5,847|
|Bolivia|0|555|230|111|896|<br>896-|
|Brazil|4,000|1,556|-385|-2,032|-861|<br>3,139|
|Chile|215|1,132|87|-3|1,216|<br>1,431|
|Colombia|1,957|952|286|0|1,238|<br>2,195|
|Costa Rica|0|134|-17|-146|-29|<br>-29|
|Cote d'Ivoire|0|502|357|-226|633|<br>633|
|Ecuador|0|858|264|-39|1,083|<br>1,083|
|Jamaica|0|154|110|-327|-63|<br>-63|
|Mexico|5,472|2,190|2,301|1,166|5,657|11,129|
|Morocco|0|949|553|-495|1,007|<br>1,007|
|Nigeria|0|1,009|704|0|1,713|<br>1,713|
|Peru|0|314|180|-52|442|<br>442|
|Philippines|525|355|928|-185|1,098|<br>1,623|
|Uruguay|0|174|-9|-113|52|<br>52|
|Venezuela|0|145|-215|0|-70|<br>-70|
|Yugoslavia|0|-59|-280|-1,171|-1,510|-1,510|
|Total|13,776|12,601|5,809|-2667|15,742|29,518|

a. Disbursements under new money packages.

Source: World Bank, World Debt Tables 1988, Vol. I, p. ixliii; Vol. II; IMF, International Financial Statistics, January 1989; and World Bank, by communication. Estimates include bank lending of $4 billion to Brazil completed in late 1988.
limited access to marital property and and male-biases in inheritance laws, owned just 19% and 9% of assets with men owning the majority of dwellings, agricultural parcels and other real estate. Land was mostly titled in the sole name of the husband.<sup>21</sup>

# **Methodology for Collecting Legal Indicators (See Annex 1)**

The database provides 0-1 indicators for measures of formal property rights, restrictions on legal capacity and constitutional protections of equality and non-discrimination. The indicators are based on provision in countries’ constitutions and statutes (usually family laws or family codes, succession acts, etc.). Countries receive a “0” if the particular right is not equal for men and for women and a “1” if women and men enjoy the same right equally. The indicators do not measure the extent of the inequality, just that there is a difference between the genders. The database covers 17 indicators. Each is reported separately; the database does not aggregate or weigh the relative importance of the indictors. More detailed notes regarding reforms, and access to the underlying data, are also available on-line (wbl.worldbank.org/timeseries).

All regions and income groups are represented in the 100 countries covered in the database (see Annex 2 for the list of countries by region). There is a concentration of countries in Sub-Saharan Africa to build on substantial legal data already collated relating to women’s economic empowerment and reflecting operational interest in the region (see Hallward-Driemeier and Hasan 2012). We track the laws for the main business city (not necessarily the capital city) and the majority of the population. In Nigeria, we cover Lagos and exclude federal laws of other states as well as laws applicable to the minority communities within the province of Lagos.

The starting point of 1960 was selected as this era encompassed the recent independence of many of the ex-colonies in Africa, East Asia and the Pacific, the Middle East and South Asia, with some exceptions. Certain countries achieved independence later after periods of conflict either splitting or reunifying – Bangladesh split from West Pakistan in 1971 and North Yemen reunified with South Yemen in 1990. The majority of Latin American countries had become independent much earlier in the 1820s and all of the ECA countries<sup>22</sup> apart from Turkey achieved independence and legal autonomy after the fall of the Soviet Union in the late 1980s. For countries that have merged, we track the laws of the ‘winning’ state from 1960 onwards. For instance we covered the laws of North Yemen for the period 1960 to 2010 which dominated the legal framework of the entire country after reunification with South Yemen in 1990. For countries that divide, they share the same indicators for the period when they were the same country and then their own separate indicators among their independence.

> 21 Deere 2013

> 22 Some countries such as Bulgaria were technically independent from the Soviet Union but fell under its sphere of influence.

7
1994). This precludes public investment, and large fraction of the population in cities has no formal water hook-up. To increase access some countries have chosen to implement BOT contracts. China, Malaysia, Thailand implemented it in water, and Chile, Mexico, in sanitation (World Bank 1997). The drawback of such privatization policy is that it increases inequality. That is, rise in public utility tariffs (to reach costs recovery level), recovery of unpaid bills and termination of illegal connexion hurt the poor. On the other hand, extension of the network favor those who are wealthy enough to access the new infrastructure. Empirical studies hence suggest that the reforms have worsened wealth and income distribution (see for instance Chisari, Estache and Romero 1999, Birdsall and Nellis 2002, Estache, Foster and Wodon 2002, Estache 2003). This in turn might explain why privatizations are so unpopular.<sup>27</sup> Privatization is a good alternative to the absence of public funds if it leads to an increase of available infrastructure such as roads, railroads, or distribution networks. Nevertheless the reforms have to be accompanied by subsidies in direction of the poor (either directly from government, or international institutions, or from the wealthy part of the consumers through cross-subsidies) to constitue genuine Pareto improvement. Last, but not least, governments with bad country risk ratings might find impossible to attract international investors on low profitability projects. They should rather target national private investors or national NGOs which are better informed on local profitability and risk.

_RM_ The second case occurs when _K_ belongs to [ _V_<sup>_min_</sup> _− V, K_ (+ _∞_ )]. When _K_ lies in this interval the market offers good ex-ante prospects to one firm. Production (with a monopoly) is always optimal. However, contrary to the low profitability case, the optimal industrial policy is non monotone in _λ_ . This is illustrated Figure 2 by the fact that the _RM/P M RM/P M_ curve denoted _K_ ( _λ_ ) is non monotone in _λ_ . Let _<u>K</u>_ denote the minimum of _RM/P M RM/P M RM K_ ( _λ_ ). For _<u>K</u> ≤ K ≤ K_ (+ _∞_ ), as _λ_ increases, the optimal industrial policy successively becomes public ownership, then privatization and finally public ownership. Indeed when _λ_ is very large the government seeks the maximal revenue from the firm. 27For instance 63% of people surveyed in 2001 in 17 countries of Latin America disagreed or strongly disagreed with the statement ”The privatization of state companies has been beneficial” (The Economist July 28-August 3 2001, p38). There is a widespread perception that they have been hurting the poor, notably through increase in tariff and unemployment, while benefiting the powerful and wealthy.

29
## **Figure 2: Per-Capita Benefits from Food Subsidies by Product (Libyan Dinars)**

<!-- Start of picture text --> 80<br>Flour<br>Flour-bread<br>Semolina<br>Rice<br>60<br>Sugar<br>Total<br>Tea<br>subsid<br>ies per Macaroni<br>capita40 Vegetable Oil<br>Paste tomatoes<br>Milk for children<br>Milk (concentrated)<br>20<br>0<br>.01 .198 .386 .574 .762 .95<br>Household Percentiles<br><!-- End of picture text --> Source: Libyan Household Consumption Survey 2007/8; Libyan authorities; and Bank staff calculations.

# **4.2.Simulation of food subsidy reforms**

This section simulates subsidy reforms and estimates the impact on household welfare and the government budget. We consider two scenarios: 1) a 30 percent decrease in the subsidy for each product and 2) the total elimination of all subsidies. Note that a 30% decrease in the subsidy on each product would result in a different price increase for each product. Table 10 reports the current subsidized price for each product under the quota regime, the unit subsidy, the price after a 30% reduction in subsidy (Final price, scenario 1) and the price after the elimination of all subsidies (Final price, scenario 2). This last price is equivalent to the market reference price that we consider for each product.<sup>13</sup> Eliminating all food subsidies (scenario 2) would result in exceptionally high price increases. The price of flour used in making bread would need to increase by almost 26 times to reach the market price, and prices of flour, semolina and rice would need to increase more than 11 times. Even in the case of the

> 13 Market prices were obtained from the authorities (Ministry of Economy) dated for the first quarter of 2013.

13
<!-- Start of picture text --> nmn)<br>=<br>ic2oOgr *<br>ae .<br>is}o<br>o<br>a<br>”<br>t2 t1 t t+1 t+2 t+3<br>Year relative to privatization<br>—e— Non-college ——®— College<br><!-- End of picture text --> <!-- Start of picture text --> n8°<br>=<br>2BeoOeer Bn 1<br>s<br>ois}<br>2 an<br>a<br>2'<br>t2 t1 t t+1 t+2 t+3<br>Year relative to privatization<br>—e— Age<36 years ——®— Age >= 36<br><!-- End of picture text --> <!-- Start of picture text --> 7<br>nSoa=<br>ic2oOgr ~ “<br>ae<br>is}o<br>2<br>8<br>t2 t1 t t+1 t+2 t+3<br>Year relative to privatization<br>—— Tenure < 5 years ——®— Tenure >=5<br><!-- End of picture text --> <!-- Start of picture text --> N<br>n a 7<br>=<br>2icoOLio<br>s |<br>ois}<br>2<br>N<br>t2 t1 t t+1 t+2 t+3<br>Year relative to privatization<br>—e— Non-managerial ——®— Managerial<br><!-- End of picture text -->
Policy Research Working Paper 10839

# **Abstract**

Global supply chains recently faced widespread disruptions. The COVID-19 pandemic caused major disruptions in 2021 and 2022, while in late 2023, geopolitical incidents in the Red Sea and water shortages in the Panama Canal disrupted global shipping routes. Regardless of the cause, delays, or rerouting mean that disruption diffuses at a global scale. To quantify and assess the magnitude of disruptions globally or locally, in 2021, the World Bank developed a proposed metric, the Global Supply Chain Stress Index. The index derives from Automatic Identification System tracking data. It calculates the equivalent stalled ship capacity measured in twenty-foot equivalent units), providing data at the port, country, regional, and global levels. This granular information can inform targeted interventions and contingency planning, improving the resilience of maritime infrastructure and networks. The index explains the observed surges in shipping rates during disruptions, assuming shippers’ willingness to pay for scarcer shipping slots. An increase of 1 million twenty-foot equivalent units in global stress pushes the Shanghai Containerized Freight Index up by US$2,300 per twenty-foot equivalent unit.

This paper is a product of the Macroeconomics, Trade and Investment 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 jarvis1@worldbank.org, crastogi@worldbank.org, ecojpr@tamug.edu and dulybina@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
# **Table IA3 – Impact of Debt Ceilings on Bank Lending to Firms (Sample of States with** **_Sustainable_ and** **_Under-Watch_ Debt)**

This table reports OLS estimates of the impact of the FD Law on bank lending to private firms for the sample of ten states classified in 2016Q1 as with “Sustainable” and “Under-Watch” public indebtedness. The variable _Volumef,b,m_ is the loan volume (in logs) issued to firm _f_ , by bank _b_ in month _m_ . _Investmentf,b,m_ is the loan volume (in logs) for investment projects issued to firm _f_ , by bank _b_ in month _m_ . _Working Capitalf,b,m_ is the loan volume (in logs) for working capital issued to firm _f_ , by bank _b_ in month _m. UnderWatchs,16Q1_ is an indicator variable that equals one for the five states that had an indebtedness classification of “Under-Watch” in 2016Q1, and equals zero for the remaining five states with an indebtedness classification of “Sustainable”. _Postm_ is an indicator variable that equals one from April 2016 onwards. Observations at the firm-bank-month level. Standard errors are reported in parentheses and are doubled clustered at the state and month levels. *, **, *** denote significance at the 10, 5 and 1 percent levels. Detailed variable definitions <u>are provided in Table A1 in the Appendix.</u>

||Volu<br>(1)|mef,b,m<br>(2)|Investm<br>(3)|entf,b,m<br>(4)|Working<br>(5)|Capitalf,b,m<br>(6)|
|---|---|---|---|---|---|---|
|Postm*UnderWatchs,16Q1|0.05***|0.04***|0.05|0.05|0.05***|0.04***|
||(0.01)|(0.01)|(0.04)|(0.04)|(0.01)|(0.01)|
|Observations|275,534|275,534|43,980|43,980|248,858|248,858|
|R-squared|0.83|0.83|0.89|0.89|0.82|0.82|
|Firm-Bank FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Bank-Month FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Sector-Month FE|No|Yes|No|Yes|No|Yes|

76
**Table 5.8: Cross-tabulation of enterprise profitability against access to modern utilities**

|(Net income of owner i|nQuetza<br>|lesper<br>|worker-hour)<br>|
|---|---|---|---|
||Basic s|ervice|Wald|
||Yes|No|Test|
|**Coverage**||||
|Electricity<br>Piped water<br>Fixed phone|8.0<br>7.9<br>15.9|3.4<br>4.7<br>4.6|***<br>**<br>***<br>|
|Cellular phone|20.2|5.2|***|
|Public phone|7.5|7.0||
|**Takeup**||||
|Electricity|7.8|3.2|***|
|Piped water|7.9|4.2||
|Fixed phone|15.9|6.2|***<br>|
|Cellular phone|20.2|6.8|***|
|**Availability**||||
|Electricity|7.7|3.5|***<br>|
|Piped water|7.4|5.0|***<br>|
|Fixed phone|11.2|4.0|***<br>|
|Cellular phone|10.6|4.4|***|
|Population size|459,|347||
|_Notes_: Refers only to ente<br>|rprises th<br>|at oper<br>|ate in dwelling.<br>|
|Null hypothesis (equality of profits between enterpris<br>Public phone variable refers to ava|es cover<br>ilability|ed and<br>of publ|not) is rejected at:<sup>***</sup>90%,<sup>**</sup>95%,<sup>*</sup>90%.<br>ic phone in census tract.|
|_Source:_World Bank calculations using the ENCOVI 2000, Institut|o Nacion|al de E|stadística – Guatemala|

However, as before, it is necessary to control for other factors affecting enterprise profitability before reaching conclusions about the role of basic infrastructure services. In addition to the variables used above, a set of variables describing the characteristics of the business is introduced. These include measures of capital and labor input, sector of activity, source of finance, and type of premises.

Once again, there are potential endogeneity problems with access variables, since it seems likely that not only does access improve profitability, but also profitability may increase the likelihood of access. This problem is addressed by instrumenting each of the utility access variables, in a series of first-stage regressions using the community availability of the service as an instrument. As noted above, it can be argued that local availability is more likely to be exogenous than household availability. It could however be argued that local availability is correlated with unobserved characteristics of the local market. In order to control for this potential effect, a series of municipality specific dummies (or fixed effects) were included in the regressions.

As might be expected, the results indicate that enterprise profitability is significantly related to the magnitude of labor and capital inputs and the type of financing facilities that are available. Utility coverage variables do not prove to be statistically significant in urban areas, perhaps because coverage of services is close to universal, and hence there is little variation from which to estimate the coefficient. In rural areason the other handcoverage of electricity, water and cellular telephones are all statistically significant with sizable coefficients. Moreover, the overall explanatory power of this model is much higher than the urban one, with an R-squared coefficient of 55% versus 15%.

43
Slovenia. Thus, the number of observations in the panel is 225 (15×15). We focus on the period starting in 1990 because we believe such selection fully covers the transition period and thus helps us gain a thorough understanding by incorporating the time trend and growth pattern of FDI inflows in the region.

With all variables converted to log form except those presented in percentages<sup>3</sup> , our benchmark regression appears as follows: ln _FDIi_ , _t_ = _b_ 0 + _b_ 1ln _CFDIt_ + _b_ 2 ln _FDIi_ , _t_ − 1 + _b_ 3 _GPCGRi_ , _t_ + _b_ 4 ln _GDPi_ , _t_ + _b_ 5 ln _WFDIt_ + _b_ 6 ln _WAGEi_ , _t_ (1) + _b_ 7 _ILLITi_ , _t_ + _b_ 8 _OPENi_ , _t_ + _b_ 9 _TARIFFi_ , _t_ + _b_ 10 _INCTAXi_ , _t_ + _b_ 11 _PSRi_ , _t_ + _b_ 12ln _TELEi_ , _t_ + _b_ 13 _ACCESSi_ + _ui_ + _vi_ , _t_ where subscript “ _i_ ” and “ _t_ ” stand for country _i_ in year _t_ and _ui_ denotes the countryspecific effects and _vit_ the disturbance term.

Our dependent variable is annual foreign direct investment inflows to the 15 CEECs. As defined in IMF (1993), direct investment refers to “investment that is made to acquire a lasting interest in an enterprise in an economy other than that of the investor, with a purpose of having an effective voice on the management level.” Such management control usually requires a minimum of 10 percent ownership of investors for the investment to be classified as direct. Our data for FDI inflows are drawn from UNCTAD interactive database.

The independent variables included in the model are expected to influence individual host country’s FDI inflows through both economic channel such as foreign trade and economic growth and environmental one with changes in institution and policy. One thing that interests us most is the use of China’s FDI inflows as a proxy for the 11