rafmacalaba/datause-encoder-data huggingface dataset:
the pricing of international equities, they perform well relative to common alternative models

# [Korajczyk and Viallet (1989)].

I use the returns on all stocks from the twenty-four national stock markets to estimate the factor-mimicking portfolios. For an average month in the period January 1976 to December 1992 there are 6851 firms with available retums from the twenty-four markets.

# **6. Measuring Deviations from the Law of One Price**

The pricing deviations discussed in Section 1 and 2 were expressed as discrepancies between an asset's true expected return and the expected return implied by the asset pricing model. However, we do not observe the true expected returns on the asset, we observe the ex _post_ return on the asset. From (4), we see that the asset's _ex post_ return deviates from its expected return due to (i) shocks from the common factors and (ii) asset specific shocks.

The assumption of an factor structure and the asset pricing theory [equations (4) and (2)] imply restrictions on a multivariate regression of asset returns on a constant and the excess returns on factor-mimicking portfolios, which are embodied in (8). The restriction is that the intercepts are jointly equal to zero. That is, in the multivariate regression: (9) a', the vector of intercept terms, are the pricing deviations. If markets are integrated and the multifactor asset pricing model describes asset expected returns a' should be equal to zero. However, if risks are priced differently across economies, these pricing differences will lead to non-zero values of a. Thus, one measure of financial integration is the size of the intercept 13
# Reference List

Alfaro, Laura, Areendam Chanda, Sebnem Kalemli-Ozcan, and Selin Sayek. 2006. "How Does Foreign Direct Investment Promote Economic Growth? Exploring the Effects of Financial Markets on Linkages." NBER Working Paper 12522. Cambridge, MA: National Bureau of Economic Research.

Anderson, Chris 2006. _The Long Tail: Why the Future of Business Is Selling Less of More_ . New York: Hyperion Books.

Asheim, Bjorn T. 2000. "Industrial Districts: The Contributions of Marshall and Beyond," in Clark, Gordon L., Maryann P. Feldman, and Meric S. Gertler (eds.), _The Oxford Handbook of Economic Geography_ . New York: Oxford University Press, 413-431.

Au, Chung-Chung and J. Vernon Henderson. 2006. "How Immigration Restrictions Limit Agglomeration and Productivity in China." _Journal of Development Economics_ 80(2): 350-388.

Berger, Suzanne and Richard Lester 1997. _Made by Hong Kong_ . New York: Oxford University Press.

Berry, Christopher and Edward Glaeser. 2005. "The Divergence of Human Capital Levels Across Cities." NBER Working Paper 11617. Cambridge, MA: National Bureau of Economic Research.

Bettencourt, Luis M. A., Jose Lobo, and Deborah Strumsky. 2007. "Invention in the City: Increasing Returns to Patenting As a Scaling Function of Metropolitan Size." _Research Policy_ 36(1): 107-120.

Boston Consulting Group. 2002. "Commercial Attractiveness of Biomedical R&D in Medicon Valley.". Copenhagen, Denmark: The Boston Consulting Group.

Bozeman, Barry. 2000. "Technology Transfer and Public Policy: A Review of Research and Theory." _Research Policy_ 29(4-5): 627-655.

Bradford, Travis 2006. _Solar Revolution_ . Cambridge, MA: MIT Press.

Bresnahan, Timothy, Alfonso Gambardella, AnnaLee Saxenian, and Scott Wallsten.

2001. ""Old Economy" Inputs for "New Economy" Outcomes: Cluster Formation 18
WPS3981 Openness, Inequality, and Poverty: Endowments Matter* Julien Gourdon<sup>1</sup> Nicolas Maystre<sup>2</sup> Jaime de Melo<sup>3</sup>

# Abstract

Using tariffs as a measure of openness, this paper finds consistent evidence that the conditional effects of trade liberalization on inequality are correlated with relative factor endowments. Trade liberalization is associated with increases in inequality in countries well-endowed in highly skilled workers and capital or with workers that have very low education levels and in countries relatively well-endowed in mining and fuels. Trade liberalization is associated with decreases in inequality in countries that are well-endowed with primary-educated labor. Similar results are also apparent when decile data are used instead of the usual Gini coefficient. The results are strongly supportive of the factor-proportions theory of trade and suggest that trade liberalization in poor countries where the share of the labor force with very low education levels (likely employed in non-tradable activities) is high raises inequality. In our sample, countries with very low education levels also have relatively scarce endowments of capital. Quantitatively capital scarcity is the dominating effect so that trade liberalization is accompanied by reduced income inequality in low-income countries. Within-country inequality is also positively correlated with measures of macroeconomic instability. Simulation results suggest that relatively small changes in inequality as measured by aggregate measures of inequality like the Gini coefficient are magnified when estimates are carried out using decile data.

### **`JEL classification: F11, F16, D3`**

### **`Keywords: International Trade, Income Distribution, Poverty.`**

## World Bank Policy Research Working Paper 3981, August 2006

``` 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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org.
```

* We thank Olivier Cadot, Sébastien Jean, Jaya Krishnakumar, Alessandro Nicita, Branko Milanovic, Marcelo Olarreaga, Mathias Thoenig, and Adrian Wood for very helpful comments on an earlier draft. We also thank Branko Milanovic for providing us his WYD data set and answers to our numerous queries.

1 University of Auvergne and CERDI: e-mail: Julien.Gourdon@u-clermont1.fr 2 University of Geneva: e-mail: Nicolas.Maystre@ecopo.unige.ch 3 University of Geneva, CERDI and CEPR: e-mail: DeMelo@ecopo.unige.ch
Table 5 Correlation Patterns in Three Sub-periods Pearson Correlation Coefficients / Prob > I R I under H0: RhO=O / Number of observations

||1978-1980|1981-1985|1986-1990|
|---|---|---|---|
||MCY|MCY|MCY|
|M1Y|0.322|0.482<br>|0.593<br>|
||0.2072<br>|0.0366<br>|0.0095<br>|
||17|19|18|
|QMY|0.358|0.399|0.748|
||0.1580<br>|0.0904<br>|0.0004<br>|
||17|19|18|
|DCPY|0.464|0.542|0.886|
||0.0603<br>|0.0166<br>|0.0001<br>|
||17|19|18|
|GNPCAP|<br>0.192|0.099|0.467|
||0.4757|0.6971<br>|0.0509<br>|
||17|18|19|

19
_3. Excel Proficiency:_ a timed test which measures the participants’ ability to write text in cells, add and delete rows and columns, sum variables, and calculate the mean of a group of scores. The score is calculated based on the participants’ ability to complete 17 Excel tasks correctly, and the score normalized to a score out of 100 based on comparisons to the performance of University of Jordan students on the same test prior to the launch of the project.

_4. Soft Skills:_ soft skills were measured by three interactive exercises. The first was based on a group exercise, in which five to eight participants were put in a group and tasked to redesign a failing amusement park in Jordan. They were each given a pre-defined role, and evaluated on how they work in groups. The second exercise was a role-playing game designed to test the participant under pressure. The participant plays the role of a customer service associate, and the evaluator, an angry customer who had purchased a computer that broke down. The participant’s goal is to calm the customer and come up with a solution within the framework of the company’s rules. The final assessment was a skills-based interview where the soft skills specialist asks questions to elicit examples of leadership, teamwork and overcoming obstacles. We form a principal component analysis of scores in the 10 soft skill categories to form a single soft skills index.

_5. Big-5 personality traits:_ personality traits were measured through a series of 300 questions assessing the following five characteristics and their sub-characteristics: analytics (complexity, breadth of interest, innovation, tolerance), extraversion (sociability, social confidence, energy level), emotions (anxiety, cooperativeness, empathy), opportunism (social astuteness, risk taking), and dependability (organization, traditional values, and responsibility) (Paunonem and Jackson 1996). We calculated the Big-5 personality traits as the mean of their sub-characteristics, and we normalized the Big-5 personality traits for ease of interpretation. In preparation of the launch of this pilot, Dr. Marwan Al-Zoubi translated the Jackson Personality Inventory Revised into Arabic and validated the Arabic version through a sample of students at University of Jordan (Al-Zoubi 2014).

In addition to these test measures, we also collected basic information that would be typically included on a C.V., such as previous work experience, college or university, and field of study. At the end of the assessment all participants were given a seven-page report of their results 11
**_PoLis ucwa Cris_** _31_

Berg and Sachs (1992) have argued that inventory accumulation may be blued downwards by ownership transformation, particularly in retail trade. Old firms close down, their inventories transferred to new firms, and the new firms may not have been caught in the statistical reporting net. This is not a problem for the derivation of the inflation bias, however, so long as the liquidation of inventories is reflected in the profit/loss accounts of enterprises.21

# Finally we use the identity

# EB * HCA + A - CF - IA

# to calculate the inflation bias.

The reason for preferring this method to calculate the inflation bias is bocas the variability in the magnitudes of the estimates of inventory accumulation is small compared to the magnitudes of the other variables (i.e. EB + IA is a big number compared to the variation in the estimates of IA).

A rough check on the reasonableness of the inflation bias estimates is as follows. Inventories in 1991 were about _15%_ of annual sales. Inflation was fairly steady during the year, and DecemberDecember industrial price inflation was 36%. Capital gains on inventories should therefore have amounted to about 5-6% of annual sales, which is just our estimate for the inflation bias in 1991. TIs approximation also works well for 1988, but less so for 1989 and 1990, when inflation was high and variable and inventories were de-cumulating; the resulting approximations of the inflation bias are considerably hiiher than those calculated using the main method presented above.

A shortcut calculation of the inflation bias in period t can be had simply by indexing costs for inflation:

- **_l,_** I c, **_Pt-V_**

where p, is the price level at time t and N is the average age of inventories, which we approximate as just one-half an assumed average inventory life. If we do this for a variety of choices of inventory life we find that for an inventory life of one month the estimate of the inflation bias is close to those calculated above for all years; an assumed inventory life of 2 months or more gives impossibly high figures for the inflation bias in 1989 and 1990.

26. **Interengly,** in the **molt affeed** year **(1990), the figures for** inventorie **hed on lJanury** reported **monthly** by **nterpris** in **socialzed** reta **trade actuay incresed** slightly in **the course** of **dth** year. **he aistl net appretly caught** more (or **larger) socialized retail tde** enterprie **as the year** progrmsed.
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<!-- Start of picture text --> T nllnand Maoro-Adjustment<br><!-- End of picture text --> WPS 1 195

- This paper a product of the Transition and Macro-Adjustment Division, Policy Research Department - is part of a larger cepartmental study on Enterprise Behavior and Economic Reform in Central and Eastem Europe. Copies of this paper are available free from the World Bank, 1818 H Street NW, Washington, DC' 20433. Please contact Emily Khine, room NI 1-065, extension 37471 (September 1993, 32 pages).

Schaffer analyzes the causes of the collapse of profitability in 1991 of the Polish enterprise sector. He explores how it affecied the govemment budget and assesses the forecasts of enterprise sector performance used to prepare the govemment's 1990 and 1991 budgets.

Schaffer attributes about half of the drop in profitability to the decrease in the inflation rate and the consequent decrease in the inflation bias in profits that results from historical cost accounting.

He attributes most of the rest of the collapse in profitability to higher labor unit costs and higher amortization allowances. When wages are endogenized in a simple model, nearly the entire collapse of profitability is explained by the changes in inflation bias and amortization allowances.

The decrease in the inflation bias and the increase in amortization allowances caused profits, and thus profit taxes, to fall, freeing up cash that could be spent on wages, causing profits and profit taxes to fall even further. This loss in government revenue was offset by increased revenues from wage taxes, which were in tum offset by an increase in wage-indexed government spending, notably on pensions.

As a result of all these changes, the government deficit increased about 4 to 5 percent of CDP - about l,alf of the fiscal swing between 1990 and 1991.

Policy options Schaffer recommends for increasing tax revenues include the following: (1) increasing the turnover tax and introducing the value-added tax that will replace it at rates that maintain the increased level of revenue; (2) increasing the social security tax rate; and (3) maintaining, but not raising, the historical costbased profit tax, an automatic stabilizer.

An obvious alternative to the profit tax based on historical cost accounting is to redress a 1991 mistake, the Indexing of amortization deductions. Schaffer recommends drastically reducing or even abolishing amortization ueductions for state-owned enterprises for fixed capital acquired before 1990 (before the start of the transition from socialism). It is odd that these firms are given a tax break on top of the free use of stateowned capital. If anytning, they should be paying for the use of the capital.

The Policy Research Working Paper Series disseminate the findings of work under way in the Bank. An objective of the series is to get these findings out quickly, even if presentations are less than fuly polished. The findings, intrpretations, **anW** conclusions in these papers do not necessar;ly represent official Bank policy.

Produced by the Policy Research Dissemination Ceiater
_Figure 3: Distribution of the RP and DTS trainees by general average HS grade_ <!-- Start of picture text --> 75 80 85 90 95<br>General average HS grade<br>RP graduates DTS graduates<br>.15<br>.1<br>Percent of sample .05<br>0<br><!-- End of picture text --> Source: _DTS Tracking Survey Data, 2015, World Bank; World Bank calculations._ 19
due to worries about deteriorations in either their own conditions or those of the banks, rather than a change in credit supply by the banks, since banks are contractually obligated to honor their prior commitments. A similar phenomenon occurred during the GFC (e.g., Ivashina and Scharfstein, 2010). However, the “dash for cash” may have been somewhat limited by credit supply to the extent that some banks exercised material adverse change clauses or stepped up enforcement of covenants, which may help explain why small firms had relatively little participation in this phenomenon (e.g., Chodorow-Reich, Darmouni, Luck, and Plosser, forthcoming).

Nevertheless, the “dash for cash” could potentially affect bank credit supply. The credit line drawdowns raised the banks’ liquidity and credit risks, and so may have resulted in reductions in bank credit supply. Several studies find these reactions, reduced credit supply to other borrowers (e.g., Greenwald, Krainer, and Paul, 2020; Acharya, Engle, and Steffen, 2021; Kapan and Minoiu, 2021). Importantly, this particular evidence related to the “dash for cash” does not provide significant support for or against the notion that bank prudential policy responses to the GFC may have reduced credit supply and marginally inhibited the “economic surprise” because these changes in supply are directly related to a different cause.

The Beck and Keil (2021) paper cited above which finds that banks more exposed to the COVID-19 economic consequences had performance issues also finds that these banks reduced SME lending other than PPP loans, and also reduced lending overall inclusive of PPP loans, which could have hindered the “economic surprise” at the margin. In contrast, Levine, Lin, and Xie (2020) find evidence that credit supplies by small banks may have aided the “surprise” at the margin with countercyclical funding to small firms that improved employment relative to what it otherwise might have been.

There is also some limited evidence on the supply of credit card debt. Examining Y-14M 59
to capture changes in overall assets, housing quality, and ownership of durable goods between 1998 and 2003.

The OLS estimates in column 1 of Panel A show that having one member migrate overseas after 1998 is associated with a 0.18 standard deviation increase in the growth of the overall assets index over the five-year interval in comparison with non-migrant households, and is highly significant at conventional levels. Over this period, households with a member who migrated domestically to another Indian state for employment experienced a gain of similar magnitude (0.13 standard deviation), although the coefficient is not precisely estimated. The null of equality between the coefficients on both types of migration cannot be rejected ( _p-value_ of 0.60). When overall asset holdings are broken out into housing quality and ownership of durable goods (Table 4, columns 2 and 3), the results in Panel A show a positive and statistically significant gain for households with members moving abroad. The gain is also positive for households with domestic migrants, although it is not precisely estimated. Again, the null of equality between coefficients for the housing quality and durable goods indices across both migration pathways is not rejected ( _p-values_ of 0.77 and 0.73, respectively).

When the number of migrants is instrumented (Panel B), the association with gains in assets is more pronounced. Households with overseas and domestic migrants experienced overall asset gains that were 1.2 and 1.3 standard deviations higher, respectively, (column 1) than those of non-migrant households. Both coefficients are statistically significant at conventional levels and the null of equality between the coefficients on both migration pathways is not rejected unambiguously ( _p-value_ of 0.95). When overall assets are separated into housing quality and ownership of durable goods (Panel B, columns 2 and 3), gains in housing quality to households with one or more international migrants are larger than the associated gains for households with domestic migrants. While the latter’s magnitude is lower and imprecisely estimated, the null of equality cannot be rejected ( _p-value_ of 0.57). On the other hand, households with one or more domestic migrants appear to have experienced 19
at firm rather than country or sectoral-level indicators of institutions, in an attempt to obtain more robust estimates of the institutional determinants of rigidity. Hence, all the regression specifications analysing institutional effects include country fixed effects, which control for unobservable country characteristics.

First, we analyse the effect of collective bargaining coverage. The WDN survey contains firm-level information on the share of employees covered by collective bargaining. The regression estimates for this variable are presented in Table 8. The estimations indicate that bargaining coverage is positively associated with real wage rigidity and insignificantly related with nominal wage rigidity. This finding is in accordance with the results of earlier empirical studies, which were based on country-level measures of rigidity (Holden and Wulfsberg, 2007; Dickens et al., 2007).

**Table 8: Downward nominal and real wage rigidity – collective bargaining coverage**

||Collective bargaining coverage|
|---|---|
||DNWR/FW<br>DRWR/FW|
|Covered workers (%)|1.010<br>1.273**|
||(0.922)<br>(0.030)|
|Observations|10309|

Notes: The table presents the estimated odds ratios for nominal wage rigidity vs flexible wage and real wage rigidity vs flexible wage. Worker skill groups, % permanent workers, % labour cost, and sector, size and country fixed effects are added in both specifications. Robust P-values in parentheses, *** p<0.01, ** p<0.05, * p<0.1. The full regression estimation is presented in Appendix 10.

In addition to bargaining coverage, we explore the effect of employment protection legislation on wage rigidity. For this purpose, we employ the EPL index, which measures the overall strictness of individual dismissals (OECD, 2004; Tonin, 2005). The values of the EPL index across the sampled countries are presented in Table 2. We cannot enter the EPL indices directly in the regressions since these country-level variables are linear combinations of the set of country dummies. Instead, we interact the EPL index with the share of permanent workers in the firm. Note that while the share of permanent employees in every country is likely to be determined by the strictness of EPL, this effect should be captured by the country dummies included in the regression. Similarly, differences in technology across sectors would require different turnover rates, and hence an optimal mix of fixed and short-term contracts. Our sectoral dummies should, to some extent, capture these differences. Thus, our regression 25