rafmacalaba/datause-encoder-data huggingface dataset:
Last, the law of motion for the distribution of firms across productivity levels must also reflect the new structure of the stochastic process and the possibility of firm exit. Formally, letting _Mt_ +1 ( _ω_<sup>_′_</sup> ) be the mass of firms with a log-productivity level less than or equal to _ω_ , the productivity distribution of firms evolves according to the following law of motion: The expression establishes that a fraction (1 _− δ_ ) _qt_ ( _ω_<sup>_′_</sup> _−_ ∆) of firms with productivity less than or equal to ( _ω_<sup>_′_</sup> _−_ ∆) survives the exogenous exit shock and transitions to a productivity level less than or equal to _ω_<sup>_′_</sup> . A fraction (1 _− δ_ ) [1 _− qt_ ( _ω_<sup>_′_</sup> + ∆)] of the mass of firms with productivity between _ω_<sup>_′_</sup> and ( _ω_<sup>_′_</sup> + ∆) survives the exit shock and jumps downward to have productivity less than or equal to _ω_<sup>_′_</sup> . There is also an inflow of new firms into this group, which is given by the mass of entrants, a fraction Γ ( _ω_<sup>_′_</sup> ) of which will feature a productivity less than or equal to _ω_<sup>_′_</sup> . Endogenous exit will be driven by the mass of firms that transition downwards from the productivity cutoff, (1 _− δ_ ) _qt_ <u>(</u> _<u>ω</u>_ + ∆) _Mt_ <u>(</u> _<u>ω</u>_ + ∆).

The introduction of new sources of demand for labor requires that we take a stand on the empirically consistent definition of aggregate labor demand that we should use to define average size in the model. Following the practice of our various firm-level databases, which define total employment of the firm as the aggregate across all of its workers, ranging from production to managerial and research positions, we measure firm size as the aggregate of employment across production ( _l_ ( _ω_ ) + _fc_ ) and innovation ( _χ_ ( _qt, ω_ )) purposes. Formally, then, average firm size in the model is given by 32
be used to predict the estimated NTB effects. To measure the content of trade agreements, we use data put together by Mattoo, Rocha, et al. (2020). This is the most comprehensive data set on the content of trade agreements, distinguishing almost 1,000 distinct characteristics. Applying machine learning tools, we use the Least Absolute Shrinkage and Selection Operator (LASSO) method for the selection of specific provisions to check for persistent patterns in the content of trade agreements for RTAs that reduce NTBs. Most interestingly, all characteristics identified by the LASSO technique share some notion of non-discriminatory NTB or refer to explicit regulations of the WTO, i.e. again trade policy that follows the MFN principle—a result that goes in line with our previous finding that TAs successfully lower NTBs, but mostly in a non-discriminatory way.

Our paper relates to the extensive literature on trade policy and NTBs as surveyed, e.g., in Ederington and Ruta (2016). We also contribute to the large and growing literature on the effects of RTAs on trade flows. Earlier work in this field has almost exclusively focused on the overall effect of trade agreements (Baier and Bergstrand 2007). In a related study, Baier, Bergstrand, and Feng (2014) show that the trade-creating effects of RTAs differ with respect to the level of economic integration: the higher the degree of integration, the larger the effects. In their early work, Baier, Bergstrand, and Feng (2014) distinguish between non-reciprocal trade arrangements, partial scope agreements, free trade agreements, customs unions, common markets, or economic unions. Baier, Yotov, et al. (2019) implement an even more flexible approach and allow RTA effects to vary not only by trade agreement but also within pairs. Finally, we contribute to a small but growing literature that uses machine learning and other related methods to study the effects of trade agreements in the gravity context (Breinlich et al. 2021; Baier and Regmi 2021).

The rest of this paper is structured as follows. Section 2 discusses the empirical approach typically used in the literature to determine NTB effects of deep trade agreements and highlights how mismeasured tariffs and globalization trends lead to upwards biased results. Section 4 shows how results change when adequately controlling for tariffs and globalization trends. Section 5 then presents our new empirical strategy to flexibly estimate separate NTB effects across all RTAs and shows the results of the Lasso variable selection procedure. Section 6 concludes.

# **2 Gravity: From Theory to Estimation**

In this section, we describe the empirical strategy that allows us to disentangle between the NTB effect and the tariff effect of trade agreements of different types of agreements. We also 4
help alleviate SME financing constraints? An extensive literature has shown that access to external financing and firm growth are shaped by a country’s legal institutions (La Porta, Lopez-de-Silanes, Shleifer, and Vishny, 1997, 1998; DemirgucKunt and Maksimovic, 1998; Beck, Demirguc-Kunt, and Maksimovic, 2005, and Beck, Demirguc-Kunt, Laeven, and Maksimovic, 2006). In other words, in countries with better institutional environments, financing obstacles are smaller and firms obtain more external financing and are able to grow faster. More importantly, recent research using firm-level data has shown that SMEs seem to benefit the most from improvements in the institutional environment. Using data from 4,000 firms in 54 countries, Beck, Demirguc-Kunt, and Maksimovic (2005) show that marginal changes in the institutional environment result in financing and legal obstacles having a smaller negative impact on firm growth, and this effect is larger for SMEs. Using a similar database, Beck, Demirguc-Kunt, and Maksimovic (2008) show that SMEs gain greater access to bank finance as a result of improvements in property rights.

In this paper, rather than focusing on firms’ perception regarding SME financing (as has been the case with most of the recent studies), we analyze the factors banks perceive as drivers and obstacles to lending to SMEs. Of particular interest is the role of the competitive and institutional environments in shaping SME lending, and more generally banks’ interest in dealing with SMEs. By institutional factors we mean the rules and regulations that affect the functioning of the financial system and influence the operation of the private sector, as well as the more general macroeconomic environment that shapes financial contracts. We compare banks’ perceptions about SMEs in Argentina and Chile.<sup>5</sup> We use a survey that covers a wide

> 5 The World Bank has also recently conducted studies of SME financing in Colombia (Stephanou and Rodriguez, 2008) and Serbia (World Bank, 2007b). Using data for a sample of banks in developed and developing countries and SMEs in Latin America, de la Torre, Martínez Pería, and Schmukler (2008)

2
# **Figure 4. Commodity consumption scenarios**

## **A. Population growth**

<!-- Start of picture text --> Percent<br>2018-27 2010-16<br>1.4<br>1.2<br>1.0<br>0.8<br>0.6<br>0.4<br>0.2<br>0.0<br>World EM7 G7<br><!-- End of picture text -->

## **C. Income elasticities of EM7 commodity consumption**

<!-- Start of picture text --> Elasticity<br>2010-16 2018-27<br>1.6<br>1.2<br>0.8<br>0.4<br>0.0<br>-0.4<br>E. EM7 commodity demand in physical units<br>Millions of tonnes Billions of toe<br>35 China Other EM7 8<br>30 7<br>6<br>25<br>5<br>20<br>4<br>15<br>3<br>10<br>2<br>5 1<br>0 0<br>2010-16 2018-27 2010-16 2018-27<br>Metals Energy (RHS)<br>Aluminum Copper Zinc Oil Gas Coal Rice Wheat Maize Soybean<br><!-- End of picture text -->

## **E. EM7 commodity demand in physical units**

## **B. Per capita output growth**

<!-- Start of picture text --> Percent<br>2018-27 2010-16<br>7<br>Faster growth Slower growth<br>6<br>5<br>4<br>3<br>2<br>1<br>0<br>World EM7 G7<br><!-- End of picture text -->

## **D. Scenario forecasts of global commodity demand growth**

<!-- Start of picture text --> Percent<br>Baseline 2010-16<br>5 Faster growth Slower growth<br>4<br>3<br>2<br>1<br>0<br>Metals Energy Agriculture<br><!-- End of picture text -->

## **F. Scenario forecasts of EM7 commodity demand growth**

<!-- Start of picture text --> Percent<br>Baseline 2010-16<br>7 Faster growth Slower growth<br>6<br>5<br>4<br>3<br>2<br>1<br>0<br>Metals Energy Agriculture<br><!-- End of picture text --> Sources: BP Statistical Review, United Nations, U.S. Department of Agriculture, World Bank, World Bureau of Metals Statistics. Note: All growth rates are averaged over the period.

A. 2018-27 are based on UN Population Projections (2017).

B. 2018-27 data are forecasts of per capita potential growth based on World Bank (2018b) and UN Population Projections (2017).

C. Predicted values based on regression coefficients in Annex Table SF1.5. Vertical lines are 95 percent confidence intervals. D.-F. To ensure comparability, 2010-16 is model-predicted commodity demand growth. The faster growth “reform” scenario assumes 0.7 percentage point higher output growth through 2018-27, while the slower growth “recession” scenario assumes 1 percentage point lower output growth for the first five years of 2018-27, based on World Bank (2018b).

E. Toe stands for tonnes of oil equivalent. Projected average annual commodity demand in billion tons of oil equivalent for energy and in millions of tonnes for metals.

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Meanwhile, man-made reservoirs, which should help control water flows, are impeded by sedimentation.

# Irrigation-Related Problems

Saliniiye Certain types of salinity cannot be blamed on the canal irrigation system and result from the mineral composition of the soil and the climate (salinity is more extensive in arid parts of the country). Canal irrigation did, however, exacerbate the problem (known as secondary salinity), notably through seepage from the canal system and subsequent evaporation; rising water tables which draw up saline groundwater; inadequate water to meet the leaching requirements of soils; insufficient attention to drainage around saline soils; and tubewells which draw on salty water.

Almost 8 percent of soil in Punjab and up to 15 percent of soil in Sindh is severely saline. While the problem does appear quite severe from the aggregate statistics, just less than 10 percent of the good quality soils are damaged. The cost of salinity in terms of lost yields is hard to evaluate. Yields have reportedly been reduced by about one-third in the case of crops grown on slightly saline areas, and moderately affected areas showed a two-thirds decrease compared with yields on nonnal land. Growth of any kind is difficult on highly saline soils.

Secondary salinity can be reversed with rehabilitation measures and reclamation measures have been undertaken. Application of gypsum to the soils, additional water for leaching, and drainage (under SCARPs) have all been effective in reducing salinity. Of course, these measures should always be evaluated in terms of the benefits they provide in increased yields relative to the cost of the measure. It is important to bear in mind that the returns to addressing the problem of severe salinity on marginal lands are likely to be quite low.

Waterlogging: Water-logging, too, may not be as severe as commonly believed, according to the soil survey. As with salinity, inherent characteristics of the soil can be as important a deterninant of the phenomenon as human activities such as irrigation. The major cause of waterlogging in the cultivated areas is excessive percolation from the canal system, which builds up the groundwater level. Also at fault are cultivation of water-intensive crops on permeable soils, obstruction of natural drainage channels, and inefficient drainage.

The latest WAPDA figures indicates that, on average, about 2 million hectares out of a surveyed area of 16 million hectares have a water table within 1.5 meters from the surface - the Soil Survey's definition of waterlogged soil.

Othe Pro Soil nutrients have been depleted. Some get washed away by irrigation water. Unchanged cropping patterns year after year are also to blame. Almost all soils are low in organic matter, and need continuous replenishment through nitrogen and phosphate fertilizer. Soils are also highly deficient in zinc, and adequate zinc levels are particularly important in rice production.

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# **Annex 1: Studies Included in the Systematic Review**

## **Impact Estimates**

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4 ceiling on these rates." For as lorig as these ceilings lasted, they put serious limitations to the effective integration of the household and enterprise financial systems as well as to the ability of all financial intermediaries to mobilize deposits from the population to finance productive sector growth.'<sup>2</sup> Very much aware of the perverse implications of the maintenance of the subsidized portfolio, over the cotirse of 1988, 1989 and 1990 the Hungarian authorities searched for and explored different alternatives to deal with the problem. The implicit financial, social and political difficulties, delayed the adoption of a solution until December 1990.

# B. The Subsidized Portfolio: Profile and Dynamics

Figure 1 shows the expected evolution of the portfolio of subsidized loans outstanding as of January 1, 1989, and its average interest rate under the assumption that the original loan contracts remain intact.'<sup>3</sup> Estimates of the interest subsidies implicit in the portfolio and their relationship to GDP are presented in Figure 2. The calculations were based on assumptions on the evolution of key macroeconomic indicators and associated projections for the rates applicable to the Housing Fund bonds (Table 1). For 1989, actual interest rate subsidic.; amounted to approximately Ft 40 billion, equivalent to near 2.5% of GDP.

**11** As of June 1990, ceilings on interest rates on household deposits were: **(i)** 22%, before taxes, for deposits for **less** than **1** year, and (ii) 26% before taxes, for deposits for **terms** longer than or equal to one year but shorter than 3 years. Deposits for 3 years or more were **not** subject to ceilings. Rates on these deposits oscillated around 27-28% before taxes. Inflation for the 12 month period ending June 1990 was **running** at about 27%. Ceilings on interest rates on household depositsof longer than six months' maturity were removed as of January **1,** 1991.

12 **The** adverse impact that acministratively set rates might have had on deposit mobilization is supponted by preliminary egtiniates in Blejer and Sagari (1991), who found that in the last few years financial savings in Hungary have become sensitive to the real level of inter at rates.

13 Information on the subsidized portfolio was limited to maturity structure and interest rates, and was available only for loans granted by N"3. These represent 95% of the total portfolio; data for the total portfolio were thus estimated as directly proportional to those of NSB. Data ..olders of the subsidized loans (i.e., distribution by level of income, age or geographic area) were not available.
But a follow up project to the 2001 White Paper by METI's Research Institute of Economy, Trade & Industry, finds no evidence that Asia's flying geese pattern of economic development has been disrupted by China. A comparison of trade patterns among countries in the region indicates that Asian trade structures are "broadly in line with their respective levels of economic development" (Kwan 2002).

Although manufactured goods now make up the bulk of China's fast expanding exports, the country's competitiveness still relies on low value added products. Even in China's fast growing IT product sector, the country's export competitiveness still lags far behind not only Japan, but also other Asian countries. There is a clear division of labor between Japan and China, with the former specializing in high value added products and the latter in lower value added products. There is little overlap, especially in the high value added categories. Consequently, Chinese exports do not directly compete with Japanese exports, rather they complement one another, the study concludes.

Japanese semiconductor manufacturers, for example, are fast strengthening their chip design and development operations in China, but they nonetheless continue to follow the flying geese trajectory. Toshiba has increased the number of engineers at its Shanghai chip development center from 40, at its start up in 2001, to 1,000 today. The Center develops software to enhance the audio and image-processing functions of system chips used in home electronics and information equipment (Nikkei Net 29 January 2002).

Toshiba is shifting chip design and development operations to China because it does not have enough software engineers in Japan, because personnel expenses for Chinese engineers are about one-fourth those of Japanese engineers, and because electronics and information equipment makers—chipmaker's largest customers—are also shifting their chip design and development operations to China. Chipmakers need to strengthen their operations in China to work closely with corporate customers in the early stages of chip design. Mitsubishi Electric Corp., Fujitsu Ltd., and NEC Corp. are all increasing staff at their Beijing chip design centers, as are Matsushita and Sony Corp (Nikkei Net 9 February 2002).

But Toshiba is also boosting the number of software engineers for system chips in Japan from 500 to 1,000. Toshiba's strategy is to develop software for semiconductors used in general electronics equipment in China, while focusing on developing state of the art technology, such as video processing, in Japan (Nikkei Net 24 January 2002).

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World Bank (forthcoming). _The Changing Wealth of Nations._ Washington: The World Bank.

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