rafmacalaba/datause-encoder-data huggingface dataset:
the end of the 1950s to starting a deep integration process into the European and global economy at the end of the 1970s and early 1980s. Spain outperformed the world average in all sectors by 2015 thanks to its integration with its European partners. This particular case of going from autarky to deep integration will serve as a good case to disentangle the role of RTAs in globalization dynamics later in this paper.

While the global economy has globalized in the last decades, these dynamics have differed across regions. In figure (4), I study the heterogeneous globalization dynamics across World Bank regions.<sup>13</sup> To cover all the countries within each region, the data is restricted to the period 1990-2015.<sup>14</sup> The results show that South Asia and Latin America and the Caribbean (LAC) come on top, while North America has a declining trend during the 2000s in manufacturing. The dynamics in North America are driven by the US and these were discussed above. The case of South Asia, while surprising at first sight, is driven by India and in line with the results in figure (3). After underperforming the world economy and having serious difficulties, India made rapid progress (starting around 1990) in integrating into the global economy and recovered the lost ground to a large extent. The case of LAC might also look surprising since this region is known for lagging in trade integration. To understand what explains these results, figure (5) carries out a more granular estimation, across LAC countries, in the manufacturing sector. It shows that Brazil, Mexico, and Argentina were the best performers during this period. The case of Mexico is intuitive thanks to its well-known integration efforts with the US and Canada, and Brazil’s dynamics were discussed above. To understand the dynamics of Argentina, it is necessary to take into account two things. First, the globalization dynamics are measured with respect to a base year, in this case 1990.<sup>15</sup> Second, Argentina started from a low level of trade integration and despite a fragile economic situation in the 2000s, its exports grew significantly. According to the World Bank’s WDI data, Argentina experienced a period of sustained export growth in which exports grew from US27 _billiontoUS_ 97 billion between 2003 and 2011. Albornoz et al. (2018) studies the period 2003-2011 and explains that while the currency depreciated with the economic crisis

> 13See table (A5) for details on World Bank’s regions classification.

> 14The data section discusses the data in more detail.

> 15The empirical strategy presented in this paper, in line with the literature, is very demanding in terms of fixed effects and does not allow estimating international trade integration in levels since all the years cannot be included due to multicollinearity issues. See Bergstrand et al. (2015), Baier et al. (2019) and Yotov (2022a) for more details on this issue.

15
I POLICY RESEARCH WORKING PAPER 2286

# Summary findings

Mehrez and Kaufmann investigate how transparency affects the probability of a financial crisis.

They construct a model in which banks cannot distinguish between aggregate shocks and government policy, on the one hand, and firms' quality, on the other. Banks may therefore overestimate firms' returns and increase credit above the level that would be optimal given the firms' returns.

Once banks discover their large exposure, they are likely to roll over loans rather than declare their losses. This delays the crisis but increases its magnitude.

The empirical evidence, based on data for 56 countries in 1977-97, supports this theoretical model. The authors find that lack of transparenicy increases the probability of a crisis following financial liberalization. This implies that countries should focus on increasing transparency of economic activity and government policy, as well as increasing transparency in the financial sector, particularly during a period of transition such as financial liberalization.

- - This paper a product of Governance, Regulation, and Finance, World Bank Institute is part of a larger effort in the institute to research governance and transparency and apply the findings in learning and operational programs. (For details, visit www.worldbank.org/wbi/gac.) Copies of the paper are available free from :he World Bank, 1818 H Street, NW, Washington, DC 20433. Please contact Diane Bouvet, room J3-273, telephone 2C2-473-5818, fax 202-334-8350, email address dbouvetrworldbank.org. Policy Research Working Papers are also posted on the Web at www.worldbank.org/ research/workingpapers. The authors may be contacted at gmehrez@worldbank.org or dkaufmann@worldbank.org. February 2000. (33 pages)

> _The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas abouit 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, anzd conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the Wor ld Bank, its Executive Directors, or the countries they represent._

Produced by the Policy Research Dissemination Center
The 2008-09 economic crisis has been the first event that has tested the industry, and it has demonstrated marked resilience. The recession forced providers to upgrade and improve their services, increasing both efficiency and competitiveness for clients. The economic downturn created only a small inflection in the industry. The two conflicting effects mentioned in the paper (the substitution effect and the demand effect) are finding a positive reconciliation in 2010. The demand for offshore services (the demand effect) continues to increase and is expected to soon reach similar growth rates as in the pre-crisis years. The substitution effect will be even stronger in the future, as new sources of demand emerge from industries with limited current participation in the sector and as suppliers gain a greater degree of specialization. Increased growth and industry consolidation will, in turn, drive expansion to new locations, creating further opportunities for developing countries.

Offshore services is one of the few global industries where some developing nations have a real competitive advantage over the developed world, owing to their low cost and educated labor force. Developing countries with a strong educational infrastructure thus have an important opportunity to enhance their economic development with this industry. Looking ahead, there is still room for new economies to emerge as offshore destinations. More activities will be offshored and more talent will be sought. This presents a great opportunity for developing countries to continue upgrading their economies to offer higher value added activities that in the past were only reserved for developed nations.

# **Bibliography**

AbhiSays.com (2009). IT Attrition Rate has Gone Down in India. Retrieved March 3, 2010, from <u>http://abhisays.com/sofware-companies/it-attrition-rate-has-gone-down-in-india.html.</u> January 31.

- ABS-CBN News (2010). Financial BPO Sets Up Shop in Philippines. Retrieved March 2, 2010, from <u>http://www.abs-cbnnews.com/business/02/17/10/financial-bpo-sets-shopphilippines. February 17.</u>

- ABS-CBN news.com (2010). BPO Targets 90,000 More Jobs in 2010. Retrieved March 8, 2010, from <u>http://www.abs-cbnnews.com/business/02/22/10/bpo-targets-90000-more-jobs2010. February 22.</u>

- Andrews, Christopher. (2008). Selling IT Services in an Economic Downturn. When Economic Conditions Are Poor, Segmentation and Positioning Matter More Than Ever. Cambridge, MA: Forrester Research, Inc.

- AT Kearney. (2007). Offshoring for Long-Term Advantage. The 2007 A.T. Kearney Global Services Location Index. Chicago, IL: A.T. Kearney.

- ---. (2009). The Future of Outsourcing in Latin America. El Salvador: AT Kearney. April 23.

- AT Kearney (2009). Geography of Offshoring is Shifting. Retrieved March 3, 2010, from <u>http://www.atkearney.com/index.php/News-media/geography-of-offshoring-isshifting.html. May 18.</u>

- Bárcena, Alicia. (2009). Competitividad: Visión de Organismos Regionales _._ Comisión

- Económica para América Latina (CEPAL). Conference: Foro de Competitividad de las Américas III, Santiago, Chile. September 28-29.

27
# **VI. LIMITATIONS**

This study focuses on the returns to schooling as measured by labor market earnings. While a useful measure, it does mean that we do not include self-employed or informal sector workers because of methodological difficulties. This is not a problem in more advanced and growing economies, but it is a limitation in countries where a substantial proportion of the population is in the informal sector. Individual country work is needed to fill that gap (see, for example, Garcia-Mainar and Montuenga-Gomez (2005).

Another potential limitation is endogeneity. The results reported here are correlations from earnings functions estimated using Ordinary Least Squares. To the extent that there are other factors that affect the schooling decision then there could be bias. To address the potential bias researchers have instrumented schooling or tried other techniques. The results reported confirm the estimates obtained here; in many cases the returns estimated using an instrumental variables (IV), which correspond to sub-populations and are therefore Local Average Treatment Effects (LATE), are typically higher than the average OLS estimate in the same country (Ichino and Winter-Ebmer (1999); Card (1995); Duflo (2001); Patrinos and Sakellariou (2006)). Therefore, we do not believe that the correlations reported here are biased, and are certainly not biased upward.

The results reported here are private returns. They are based on what the individual will earn and the only costs considered are those incurred for attending school – fees, tuition and so on, as well as the indirect or opportunity cost of schooling in the form of foregone earnings. These estimates can help explain individual behavior about schooling decisions and can be used by policy makers to design school finance policies, especially for tertiary education. But for most policy decisions, policy makers would need to know the social returns to schooling. First, this would require full social returns estimates of social benefits (externalities and non-market effects), a difficult task for a single country (but see Acemoglu and Angrist (2001); Wolfe and Haveman (2002)), almost impossible for the global estimates we provide here. Second, one would need full social costs, in the form of what the government provides in terms of the supply of schooling. For narrow returns, one can use the private benefits and the social costs. This is something our future research will address.

# **VII. CONCLUSION**

Our new data set of comparable estimates of the returns to schooling and to potential experience covers 139 economies. We use 819 harmonized household surveys to provide the estimates that cover the period from 1980 to 2013. This compilation of comparable estimates addresses several issues in the literature, such as: (i) the definition of the dependent variable—which we keep consistent throughout; (ii) the variables used as controls – we use the basic Mincerian specification; (iii) sample definitions – we limit the analysis to the same samples throughout in terms of age, employment status and earnings; and (iv) estimation method – which we apply consistently to every survey.

18
23

**Fig. 2.4.** Needs for better housing, actual plans to move and structure of demand (% households polled)

<!-- Start of picture text --> 100%<br>90% -<br>80% 9 = 98-2<br>70% _ T___T 7 i__E__9_T E_<br>M3 no plans, no need<br>60%<br>13 no plans, need housing<br>60%<br>o plan to receive tree housing<br>40%-334 27<br>housing Theywerequitereparedtopayt 37.9 37i1 M plan to purchase(exchanget<br>30% - 20an housing<br>20% - 9.2<br>10%<br>0% ", - 144<br>1993 1996 1994 1996 1994 1996<br>Moscow Vladimir Gorodets<br><!-- End of picture text -->

**Sources:** Household **Survey** in **Seven** Cities, Moscow, December 1993; The Moscow Longitudinal Household **Survey,** January 1996; **Vladimir and Gorodeu Longitudinal Household** Survey, **Oct-1994** and Dec.1996.

It is clear from the survey data presented here that market ideas regarding housing search methods are beginning to penetrate the mentality of the Russian public. In our opinion, the widely-held view that most Russian households are convinced that housing should be free and are thus opposed to the market is erroneous. The findings of surveys conducted in the mid-1980s (Kalinina and Kosareva, 1989; Guzanova, 1989; Guzanova, 1990) show that even then, many households did not mind using their own money to buy housing. They were qite prepared to pay to move into larger apartments or to join cooperatives, and this created high demand _for_ cooperative housing. Recent studies show that as soon as the oppohrunity to buy and sell housing appeared, many households began to display the intention of solving their housing problems through market methods.

## **2.2.2 Factors influencing household attitudes** to housing market **strategies**

The following factors were taken into account in the analysis of households' prospects of dealing with the housing problem: how pressing the problem is (i.e., the level of the household's provision with housing); the income level; and the demographic structure of the household.

# **a.** **_Level of provision with housing_**

Sociological surveys commnonly show that the main reason why households do not like their living conditions is the small size of their apartments. The urgency of the housing problem strongly influences households' plans. For instance, in the quintile with the lowest general space per person the share of households that have plans to improve their housing conditions in the near future reaches 48.2%/ in Moscow, 41% in Vladimidr and 3 1.7% in Gorodets (Fig. _2.5)._
analysis of NTMs, the statistics were done only on total NTMs without breakdown by type of NTM.

# **4.3 Defining the “poor” or “excluded”**

In this study, economic “poverty” is measured as a relative phenomenon based on the analysis of income/consumption for the entire distribution by decile group. Consumption expenditure is widely accepted as a proxy for income owing to the difficulty of getting reliable quantitative data on household income through direct enquiries in household surveys. Additional variables in the data enabled us to also look at groups traditionally excluded from the process of economic growth – women, those working in rural areas and those employed in the informal sector.

# **5. Results**

# **5.1 Tariffs faced in the export market are inversely related to income**

Using household level data, the average income (using consumption as proxy) and tariff faced in export markets for each income decile were calculated (Table 1). Households in the poorest decile have an average weekly consumption of only 511 rupees ($9.60), while households in the richest decile consume ten times that amount.

Table 1: Average tariff faced by income decile based on household weekly consumption.

|Income<br>Decile|Household W<br>|eekly Income<br>|Average Tariff<br>Faced (%)<br>|
|---|---|---|---|
||Rupees|US $|Simple*|
|1|511|9.6|24.4 a|
|2|783|14.8|22.9 b|
|3|962|18.2|22.4 b|
|4|1130|21.3|21.5 c|
|5|1305|24.6|20.3 d|
|6|1504|28.4|19.2 e|
|7|1761|33.2|18.4 e|
|8|2118|40.0|17.5 f|
|9|2713|51.2|16.0 g|
|10|5112|96.5|14.5 h|

* Using Duncan's test on the average tariff faced. Average tariffs are significantly different across deciles except when they are tagged with the same letter of the alphabet.

The results show that goods associated with higher income households face lower tariffs while goods associated with low income households face higher tariffs. In the table, the tariff faced by the next higher income decile is consistently and significantly lower except for two neighboring deciles – the difference between tariffs for deciles 2 and 3, and for deciles 6 and HS correlation code. This is mainly an issue related to services sectors. The study, therefore, is largely limited to merchandise sectors.

9
# **1 Introduction**

India has aggressively pursued food security for many years. For India’s policy makers, the prices of staple foods—particularly wheat and rice—raise major concerns. To protect poor consumers from high prices, and to lower the cost of food in normal times, a Public Distribution System (PDS) provides food to low-income consumers at concessional prices. To protect producers from low prices, a pre-announced Minimum Support Price (MSP) places an effective floor on domestic prices, defended by the government’s accumulation of staple food stocks. India also pursues an active trade policy to insulate the domestic market from fluctuations in world prices of these staples. Together, these policies have been quite successful in stabilizing domestic prices, but concern is growing over the policies’ mounting costs, potential inefficiencies, and the stark juxtaposition of large and growing public stocks with rising food prices (Basu 2011).

Concern about food prices is common in countries with many poor people who are vulnerable to price spikes or price slumps. In that context, policy makers often favor policies that reduce the volatility of staple food prices. Such policies have been especially prevalent since the 2007/08 world food crisis, which highlighted the potential instability in world food markets (Demeke, Pangrazio, and Maetz 2009; Gouel 2014).

This study looks at alternatives to address some of the challenges facing policy makers in these situations. Based on the assumption that policy makers seek to maximize social welfare, and specifically taking into account their dislike for price volatility, this study assesses current policies for wheat in India and then examines alternatives. The analysis relies on a rational expectations model of storage and trade that represents two regions—India and the rest of the world—and their interaction on the wheat market. The economic agents in the model include producers, consumers, and holders of stocks. Producers base their planting decisions on expected prices at harvest time. Stock holders make decisions on how much to store from one year to the next based on the price they expect next year, the price of grain this year, and the cost of storage. International trade is represented by spatial arbitrage conditions. Current policies are incorporated by identifying patterns that enable them to be represented as simple rules, defined as functions of world and domestic conditions. The model is calibrated using 2012 data on India’s wheat market and solved numerically.

Alternative stabilization policies are designed based on the maximization of a social welfare function that includes a quadratic loss function in prices. In addition to a fully optimal policy, which gives welfare-maximizing levels of storage and trade in all situations, the use of simple rules of intervention is also considered. Past research suggests that simple rules might yield a large share of the benefits of an optimal policy (Gouel 2013c) while being easier to design and to 5
# **The financial sector is ready to meet the challenges**

We all face great challenges to improve access to financial services: the financial institutions; the government; the regulators and the users of the financial system.

For the financial sector the challenges are: first recovering public trust as financial intermediaries; second, continuing to improve the quality and efficiency of day-to-day service delivery. Recent surveys suggest that there has been tangible progress in this area. Sector studies report that the cost of managing $Col 100 have dropped from $6.2 five years ago to $5.8 today.

Third, maintaining the process of technological innovation in service delivery and meeting the consumers’ needs.

Finally, building a stable institutional framework, since it is clear that a healthy business environment is essential to financial sector depth. And here the government must play a fundamental role.

Factors such as the guaranteed creditor rights, a stable regulation framework, interest rates based on market realities, an efficient judicial system, market transparency based on public disclosure of financial information and clear accounting regulations are crucial<sup>4</sup> for this development. How does Colombia fare in each of these points?

a. According to an IDB study of indicators of credit risk, Colombia has one of the worst ratings of protection to creditors, along with Peru and Mexico<sup>5</sup> ; this necessarily means higher transaction costs and generates inefficiencies in financial intermediation.

b. Regarding a stable regulatory framework, the most impeding issue is the current tax on financial transactions. Initially it was meant as a “short term measure”, with a tax of 0.2% on financial transactions; today, we find ourselves with a permanent tax of 0.4%.

We have repeatedly remarked the negative effects of this tax on the overall economy: it has greatly reduced the average returns on savings, making them less attractive; it has increased preference for cash transactions and has generated an increase in the “unbanked” population. The tax on financial transactions has effectively set back the Colombian economy by fifty years; preference for cash has grown and intermediation has shrunk.

> 4 De Nicoló, Gianni, Geadah, Sami y Rozhkov, Dmitriy. “Cómo cerrar la “gran brecha”

> 5 BID (2001), “Mercado financiero para el crecimiento empresarial” en Competitividad, El motor de desarrollo del crecimiento, Washington DC

13
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