rafmacalaba/datause-encoder-data huggingface dataset:
# **Table 9: Priority of Secured Creditors vis a vis Others Creditors in**

# **MENA and Regional Comparison**

|**Secured Cr**|**editors Have**|**Priority Over**|**Secu**|**red Creditors Do**|**Not Have Pr**|**iority Ov**|**er Statutory**|
|---|---|---|---|---|---|---|---|
|**Statutory **|**Claims(Taxes**|**and Wages)**||**Claims**|**(Taxes and**|**Wages)**||
|Iraq and Jordan|||Alger<br>Oman<br>and G|ia, Bahrain, Egypt,<br>, Qatar, Saudi Ara<br>aza, Yemen|Iran, Kuwait,<br>bia, Syria, Tu|Lebanon,<br>nisia, UEA|Morocco,<br>, West Bank|
||**East Asia**<br>**& Pacific**|**Europe &**<br>**Central**|**High**<br>**income:**|**Latin**<br>**America &**|**Middle**<br>**East &**|**South**<br>**Asia**|**Sub-**<br>**Saharan**|
|||**Asia**|**OECD**|**Caribbean**|**North**<br>**Africa**||**Africa**|
|**Legal Right**<br>**Index (0-10)**|**5.7**|**6.6**|**6.8**|**5.5**|**3.3**|**5.3**|**4.6**|
|Absolute<br>priority outside<br>bankruptcy|58.3|75.0|59.1|38.1|16.7|14.3|25.6|
|Absolute<br>priority in<br>bankruptcy|33.3|71.4|59.1|4.8|11.1|14.3|15.4|
|**Average**|**61.7**|**65.4**|**67.3**|**45.2**|**29.4**|**54.3**|**49.5**|

_Source: Doing Business_ 2010

# _2.6 Enforcement of security interests: seizure of secured assets in cases of loan default_

Speedy, effective, and inexpensive enforcement mechanisms are essential to realizing security interests. Enforcement is most effective when parties can agree on rights and remedies upon default, including seizure and sale of the collateral outside the judicial process. Reasonable safeguards against creditor misbehavior should be adopted to ensure that self-help remedies are exercised peacefully and that commercially fair value is obtained through private sale of the collateral. When the seizure and disposition of the collateral does call for judicial intervention, expedited summary legal proceedings should limit judicial findings to the existence of agreement granting the security interest and of an event of default. An efficient procedure is particularly important in the context of movable property, which in most cases depreciates in value over time. Despite the importance of this part of the process, enforcement/execution is often the weakest link in the chain in the system of secured transactions. Difficulty in execution is often reported as a significant barrier to access to credit.

24
**Table 5 Index of the Average Wage of Exports**

_<u>trade-weighted average PRODY</u>_

|_Exporter _|_1990–94_|_2000–04_|_Change_ (%)|
|---|---|---|---|
|East Asia and the Pacific|9,604|11,001|14.5|
|China|8,308|9,963|19.9|
|Latin America and the Caribbean|8,143|9,128|12.1|
|World|10,679|11,108|4.0|

_Source:_ Freund 2006.

_Note:_ The data have been calculated using the PRODY index in 2000–04, weighted by the average industrial trade share of the respective region (or country) over the period.

While it would be expected that China’s success would affect countries at similar stages of economic development, factor abundance, technological capability, and production costs, the fact that China is exporting more sophisticated products than its income level implies suggests that the potential impact may be larger on more advanced economies in East Asia. An important caveat is that it may appear that the NIEs are losing market share to China in third markets, but this does not account for the fact that the NIEs are exporting through their foreign affiliates in China; so there is a reshuffling in production strategies (from the NIEs to China) rather than a loss in exports. More than half of China’s exports in high-technology products are undertaken by foreign firms (see figure 19). The next section looks at the impact of China on the NIEs and Southeast Asia.

<!-- Start of picture text --> Figure 18 PRODY, 2000–04 Figure 19 China’s High-Technology Trade by<br>Category of Firms<br>GDP per capita share in tot al export s import s<br>30,000 100%<br>90%<br>25,000 Singapore<br>80%<br>20,000 70%<br>Korea<br>60%<br>15,000<br>50%<br>10,000 40%<br>Malaysia<br>Thailand<br>30%<br>5,000 Indonesia China<br>20%<br>Vietnam Philippines<br>- 10%<br>4,000 5,000 6,000 7,000 8,000 9,000 10,000 11,000 12,000 13,000 0%<br>1997 2003 1997 2003<br>4-digit PRODY<br>Chinese f irms Joint Vent ure Fully foreign owned f irms<br>Source: Based on calculations by World Bank staff. Source: China, General Administration of Customs,<br>Note: The 4-digit PRODY is the trade-weighted average in 2000– various.<br>04.<br><!-- End of picture text --> The export performance of the East Asian economies has been remarkable. Merchandise exports have increased by a factor of 13 since 1985, more than twice the rise in world exports. Chinese exports have done even better, surging by more than a factor of 20 over this period. What has been the impact of China’s rapid export expansion on the rest of East Asia? In which industries and which markets is the competition from China greatest? There are many significant industries where East Asia has lost market share and China has gained market share, as seen by the number of dots in the lower right quadrants in figure 20.<sup>17</sup> 19
26 level of imports as the NTM in place, and use this as the basis of aggregation. Measurement methods of the trade impact of NTMs generally use a partial equilibrium approach and, in addition to utilizing either the direct or indirect approach (see Section 2.3.1), rely on either price or trade volume data.<sup>14</sup> Examples of the indirect approach using price data involve some of the first attempts to assess the trade impact of NTMs by comparing the domestic price of a good with its international price to obtain an estimate of the price gap (Andriamananjara et al., 2004 or Bradford, 2003). The underlying idea is that non-tariff measures, just like tariffs, drive a wedge between the two prices. A simple expression of the tariff equivalent (TE) of NTMs calculated through the price gap approach is: where �� is the domestic price, �� is the world price (both net of wholesale and retail margins), _t_ is the ad valorem tariff and _c_ is the international transport margin also expressed in ad valorem terms. Thus, the severity of NTMs as barriers to trade is inferred from any remaining price gap (after controlling for direct trade barriers). In contrast, Dean et al. (2009), while also using data on international price gaps, utilizes the direct approach which requires observable data on NTM incidence. This paper estimates the impact of observable NTMs on price gaps (controlling for a number of factors, including observed differences in local markups, tariffs and transport costs). Obviously a key issue in these approaches involves obtaining the relevant price information.

An application of the indirect approach which uses information on trade volume is undertaken by Chen and Novy (2012). This paper uses a gravity model to infer bilateral trade frictions from observable trade data by comparing actual trade flows and predicted trade flows in the absence of non-tariff measures. They then show that NTMs such as product standards are highly correlated with these inferred trade frictions.

Finally, the most common approach is to estimate directly the impact of non-tariff

> 14 Computable General Equilibrium (CGE) models, such as the Global Trade Analysis Project (GTAP), can in principle be used to assess the impact of non-tariff measures. However, the various treatments of NTMs in CGE models present a series of problems that have limited their use in the literature. See Fugazza and Maur (2008) for an overview.
higher for foreign firms ( _expsh_dir_ ), while the share of direct exports shows a negative coefficient sign, but has no statistically significant impact.

In sum, we find that foreign investors tend to outperform domestic producers in terms of sales, firm size, productivity, technology gap, exporting behavior, and direct export share. This would imply a higher knowledge and productivity spillover potential compared to domestic firms.

**Table 2: Performance Indicators, Foreign Investors vs. Domestic Producers (Mean Difference)**

|**Variable**|**Definition**|**Difference**<br>**(1)**|**Additional**<br>**controls for**<br>**ln****_emp_**<br>**(2)**|
|---|---|---|---|
|ln_sales_|Firm's sales (USD) in natural logarithms|2.5893***<br>(0.000)|2.1162***<br>(0.000)|
|ln_age_|Number of years since firm has started operations in|-0.1429|-0.2192|
||natural logarithms|(0.389)|(0.233)|
|ln_emp_|Firm’s number of employees in natural logarithms|0.3410|n.a|
|||(0.270)|n.a.|
|ln_labprod_|Firm's sales per number of employees (USD) in natural|1.9528***|2.1162***|
||logarithms|(0.000)|(0.000)|
|_tech_|Technology gap between firm and its leading domestic|-0.4982***|-0.6094***|
||competitor in the same sector, where 1 means “not existent”<br>and 4 means “large”|(0.003)|(0.000)|
|_emp_ter_|Percentage of workers with tertiary education in the firm's|6.5680|8.9122|
||workforce|(0.262)|(0.106)|
|_emp_sec_|Percentage of workers with secondary education in the firm's|-6.7298|-7.8271|
||workforce|(0.315)|(0.225)|
|_export_|Dummy taking the value of 1 if a firm exports, and 0 otherwise|0.6418**|0.5233*|
|||(0.025)|(0.083)|
|_expsh_dir_|Percentage of direct exports of firm's total sales|35.7146***<br>(0.000)|33.3476***<br>(0.000)|
|_expsh_ind_|Percentage of indirect exports of firm's total sales|-1.6483|-4.8535|
|||(0.681)|(0.206)|

Source: Own calculations. p*<0.1, p**<0.05, p***<0.01 (p-values in parentheses). Note: Variables refer to FY 2012. All regressions control for country-sector fixed effects. Standard errors are robust to heteroscedasticity.

# **_Linkages with the Local Economy_**

Table 3 compares foreign investors’ and domestic producers’ linkages with the local economy. Linkages are measured in terms of the share of domestic inputs and workers as well as a firm’s percentage of sales going to the domestic market. All are expected to increase the potential of positive spillovers for local suppliers (see section 2.1). We also examine differences between types of inputs and workers. We follow the specification of the previous section. All variables refer to FY 12
Policy Research Working Paper 8668

# **Abstract**

This paper estimates the effect of worldwide tax changes on output following the narrative approach developed for the United States by Romer and Romer (2010). The analysis uses a novel dataset on value-added taxes for 51 countries (21 industrial and 30 developing) for the period 1970–2014 to identify 96 tax changes. It then uses contemporaneous economic records to classify such changes as endogenous or exogenous to current (or prospective) economic conditions. In line with theoretical distortionary and disincentive-based arguments, and using only exogenous tax changes, the main finding is that the effect of tax changes on output is highly non-linear. The tax multiplier is essentially zero under relatively low/moderate initial tax rate levels and more negative as the initial tax rate and the size of the change in the tax rate increase. Based on a global sample, these novel non-linear findings suggest that the recent consensus pointing to large negative tax multipliers in industrial countries, particularly in Europe (e.g., Alesina, Favero, and Giavazzi, 2015), (i) is not a robust empirical regularity, and (ii) is mainly driven by high initial tax rates in these countries. The paper also shows that the bias introduced by misidentification of tax shocks critically depends on the procyclical or countercyclical nature of endogenous tax changes. The relevance of the arguments is evaluated both for the novel global sample and for Romer and Romer’s U.S. dataset.

This paper is a product of the Office of the Chief Economist, Latin America and the Caribbean Region. 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/ research. The authors may be contacted at gvuletin@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
remarks (Section 4). Appendix A has a full mathematical statement while Appendix B introduces the interface and Appendix C presents additional simulation results in tabular form.

# **2. Non‐technical overview of model structure and database**

GEM‐Core is a single‐country recursive‐dynamic general equilibrium model designed for medium‐ and long‐run policy analysis. It is a multi‐purpose model in the sense that it can analyze policies in a wide range of areas including growth, fiscal space, and external shocks. It can also be applied to databases with different disaggregations. A typical simulation period is 5‐20 years. However, the period is highly flexible, ranging from comparative statics to very long periods, and should be determined by the purpose of the analysis.

This section provides a non‐technical overview of GEM‐Core and presents its macro database, structured to meet the needs of the model.<sup>2</sup> (A detailed mathematical statement of GEM‐Core is found in Appendix A.) This presentation assumes that the model is applied to a database based on the macro SAM in Table 2.1. For illustration, we use data for a representative (or archetype) low‐income country for 2015.<sup>3</sup> [Cicowiez and Lofgren (2017a), provide details regarding the building and interpretation of the SAM in Table 2.1.] The disaggregation of the accounts of the SAM defines the disaggregation of the database and the model application, i.e., it is here disaggregated into two activities and commodities (private and government), two factors of production (labor and private capital), and three institutions (household, government, and rest of world). As indicated by the SAM, each institution has not only current but also capital accounts, something that makes it possible for the model to cover issues related to the financing of current activities and investment. The SAM also depicts the structure of taxation via a set of disaggregated tax accounts.

> 2 GEM‐Core is part of GEM suite, a set of models with a common core and extensions in selected areas. The model is a descendant of MAMS (Lofgren et al. 2013).

> 3 More specifically, the data shown are the weighted average of macro SAMs for the 17 low‐income countries for which sufficient information was available in cross‐country databases. Each SAM was weighted by its share of GDP at market prices at current US dollars for the countries included.

‐3‐
# Control Study Timing Mean

Short-run effects Laos -2m_ -.1837 Heterogeneity: t? = 0.00, I? = .%, H?=. Test of 8, = 8;: Q(0) = 0.00, p=. Test of 8 = 0: z= 0.54, p= 0.59 Effect size Weight with 95% CI (%) 0.03 [ -0.08, 0.14] 14.79 0.03 [ -0.08, 0.14]

## Medium-run effects

Egypt Community lm O01 EgyptInfrastructure 4m _ -.016 Tunisia 12m 263 Rural DRC 12m -.017 Egypt Community 27m -.04 Tunisia 66m 162 Heterogeneity: t? = 0.05, I? = 94.28%, H? = 17.49 Test of 8, = 8;: Q(5) = 160.72, p = 0.00 Test of0 = 0: z= 2.54, p= 0.01

# Overall

0.15 [ -0.02, 0.33] 13.55 -0.01 [ -0.05, 0.03] 15.66 —i— 0.29 [ 0.12, 0.45] 13.63 +E 0.62[ 0.53, 0.71] 15.07 0.11 [-0.01, 0.24] 14.53 —i— 0.28[ 0.07, 0.48] 12.76 << 0.24[ 0.05, 0.42] i 0.21 [ 0.04, 0.37] Heterogeneity: 1? = 0.05, I? = 94.28%, H? = 17.48 Test of 0, = 0,: Q(6) = 162.32, p = 0.00 Test of8 = 0: z= 2.45, p= 0.01 Test of group differences: Q,(1) = 3.66, p = 0.06

-0.1 0 0.10.20.30.40.50.6 0.7

Random-effects REML model
Policy Research Working Paper 8486

# **Abstract**

The literature suggests a wide range of impacts of improved transport connectivity on agricultural growth. Still, the infrastructure-growth nexus remains somewhat mysterious, particularly in the African context, because many rural farmers do not have their own transport means. Using data from Madagascar, the paper reexamines the important roles of agrobusinesses. By applying the spatial autoregressive model, it is shown that proximity to input-oriented agrobusinesses, such as input dealers and equipment suppliers, is particularly important to increase rice production. Fertilizer and irrigation use is also found important, indicating the needs for intensification in rice production. Market accessibility is always found as a significant determinant: transport infrastructure connecting farmers and markets, especially the capital city, Antananarivo, is therefore important to develop and maintain.

This paper is a product of the Transport and Digital Development 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/research. The authors may be contacted at aiimi@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
35 (1982), also face the problem of how to reduce large distortions in relative prices, as well as the distortions resulting from heavily regulated or almost non-existing labor and financial markete. On top of these distortions, there 6xists the additional burden of a large public enterprise sector with low response to price incentives, and a lack of institutions to manage macroeconomic policies and establish a minimum set of rules for the normal functioning of a market economy (i.e. property rights, bankruptcy laws, appropriate accounting procedures etc.).

For a country that is about to initiate a major reform effort, the question that has to be faced from the beginning is the sequence and speed of other reforms. Any reform that calls for a major reallocation of resources will need to deal with appropriate and credible relative prices early on. In countries that have much to gain from an integration in the world economy, like Mexico (1982), Chile (1973) and the Eastern European countries todayp trade reforms have a very high priority. The initial stages of a trade reform, such as the replacement of managed trade by open trade, the replacement of QR'e for tariffs, and the reduction of extreme tariffs, should be attempted early in the reform procese. However, major trade liberalization should be attempted only when clear and credible progress has been achieved in reducing inflation or when there is a clear perceived commitment from the authorities that the anti-inflationary program has a very high priority. In countries with a very uncompetitive domestic economy, trade liberalization may help the stabilization effort, as could be the case of Mexico (1988) and Poland (1990), however, a major fiscal adjustment is necessary to generate appropriate spending reduction and to avoid a balance of payments crisis.

Trade reforms aim to shift investment and labor from nontradable and highly protected Import competing activities toward the export oriented and
The difference between the observed and simulated poverty, _P_ αι − _P_ α , can be thought of as the amount of poverty reduction attributed to the _maquila_ premia, employment, or both, depending on the simulation.14 Because both the _maquila_ premia and the jobs created by this sector had positive income effects, it will come as not surprise that these impacts reduce poverty. The aim of the exercise is to quantify the importance of the _maquila_ industry for poverty alleviation in Honduras.

Three simulations are run, two of which capture the poverty effects attributable to the _maquila_ wage premia (as shown in specification 3b in table 6) and one of which creates a hypothetical world in which Honduras had no _maquila_ jobs. In the first simulation, the year-specific _maquila_ sector wage premia are subtracted from wages of all _maquila_ workers (table 8). This counterfactual captures the difference between the observed poverty headcount and the headcount ratio that would have prevailed in Honduras had _maquila_ workers not enjoyed a premium like the one shown by specification (3b) in table 6. The second simulation captures the poverty effects of the _maquila_ sector wage premium, including its effect through gender. In this simulation both sets of _maquila_ premia (the _maquila_ effect and the _women*maquila_ effect in table 6) are subtracted from the wages of women in the _maquila_ sector.<sup>15</sup>

**Table 8. Estimated Poverty Headcounts in the Absence of** **_Maquila_ Effects, 1991–2006**

|_Headcount ratio_|_1991_|_1995_|_2001_|_2006_|
|---|---|---|---|---|
|Actual|79.9|75.1|70.9|67.0|
|Without_maquila_premium|||||
||80.0|75.1|71.5|67.6|
|Without_maquila_and gender|||||
|premia|80.1|75.3|71.6|67.6|
|Without premia and_maquila_|||||
|employment|80.5|75.9|73.0|69.4|

_Source_ : Authors’ estimates. _Note_ : Poverty is measured using a moderate poverty line. Simulations are based on estimated parameters from specification (3a) in table 6.

Given that all parameters measuring wage premia in the _maquila_ sector are nonnegative, it is not surprising that eliminating them increases poverty. If the _maquila_ sector had not paid a premium, the moderate national poverty headcount in 2001 would have been 71.5 percent instead of the observed level of 70.9 percent; if the premium enjoyed by women in the _maquila_ sector had also been eliminated (together with the interaction effect), the poverty headcount would have risen to

> 14 Nicita and Razzas (2003) estimate a model with enough economic structure to capture the employment effects associated with a boom in the textile and apparel industry. The authors find that for each new job created in the textile industry, 4.5 individuals experience an increase in their purchasing power.

> 15. Because only significant parameters were taken into account in this microsimulation, the _maquila_ effect in 1995 is equal to zero.

15