rafmacalaba/datause-encoder-data huggingface dataset:
Policy Research Working Paper 9204

# **Abstract**

This paper uses data from the National Financial Inclusion Survey 2018 to understand the determinants of financial inclusion in Sri Lanka and their significance for inclusive growth. The findings highlight that gender, education, and formal employment are important determinants of financial inclusion in the country. The results indicate that being a male, having better education, and having formal employment increase a person’s access to, and usage of, formal finance. The results also suggest that despite high levels and gender parity in education, Sri Lankan women seem to access more informal finance (and less formal finance) compared with men. There is a general lack of familiarity and low use of digital finance among women. Comparative analysis using the World Bank Group’s Global Financial Inclusion (Global Findex) Database 2017 indicates that although Sri Lanka leads its regional peers in access to finance, it lags its more aspirational East Asian counterparts in usage of savings and credit products as well as digital finance. The paper’s findings complement recent policy initiatives such as the National Financial Inclusion Strategy for Sri Lanka. The findings also help in designing targeted actions to address the remaining gaps in financial inclusion in Sri Lanka.

This paper is a product of the Finance, Competitiveness and Innovation 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 tarandara@ifc.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
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**<u>Table 4:  Family Management and Management Practices by Income</u>**

|**Model**||**OLS with Countr**|**y FE (Cross-section)**||
|---|---|---|---|---|
|**Outcome Variable**||**Overall Man**|**agement Score**||
||**Low and Middle**<br>**Income Economies**|**High Income**<br>**Economies**|**Low and Middle**<br>**Income Economies**|**High Income**<br>**Economies**|
||**(1)**|**(2)**|**(3)**|**(4)**|
|Share of family management (0 to 1)|-0.057*|-0.026|||
||(0.029)|(0.019)|||
|All management is family Y/N|||-0.045**|-0.043***|
||||(0.021)|(0.015)|
|Share of same family ownership (0 to 1)|0.026|0.006|0.013|0.019|
||(0.027)|(0.021)|(0.021)|(0.019)|
|Owner, Manager or Board Political Connection Y/N|0.004|-0.051|0.005|-0.049|
||(0.024)|(0.037)|(0.024)|(0.037)|
|Female top manager Y/N|0.010|0.010|0.011|0.013|
||(0.014)|(0.017)|(0.014)|(0.017)|
|Firm Formally Registered when Started Operations|0.045|0.044|0.045|0.044|
||(0.029)|(0.033)|(0.029)|(0.032)|
|Top manager experience in sector (years)|-0.001|-0.0004|-0.001|-0.0004|
||(0.001)|(0.001)|(0.001)|(0.001)|
|Log of age of firm|-0.015|-0.014|-0.015|-0.015|
||(0.010)|(0.013)|(0.010)|(0.013)|
|Log of size|0.036***|0.034***|0.036***|0.033***|
||(0.005)|(0.008)|(0.005)|(0.008)|
|Direct exports 10% or more of sales Y/N|0.023*|0.046***|0.023*|0.045***|
||(0.013)|(0.014)|(0.013)|(0.014)|
|Foreign ownership Y/N|0.017|0.038**|0.018|0.037**|
||(0.016)|(0.015)|(0.016)|(0.015)|
|Establishment has checking or savings account Y/N|0.027|-0.026|0.030|-0.023|
||(0.022)|(0.059)|(0.022)|(0.060)|
|Establishment has a line of credit or loan Y/N|0.021*|0.040***|0.021*|0.039***|
||(0.012)|(0.014)|(0.012)|(0.014)|
|ISO Certification Ownership Y/N|0.050***|0.064***|0.050***|0.063***|
||(0.015)|(0.015)|(0.015)|(0.015)|
|Firm identifying labor regulations as a major or severe<br>constraint Y/N|-0.044**|0.030|-0.044**|0.032|
||(0.020)|(0.023)|(0.019)|(0.023)|
|Manufacturing Sector Y/N|-0.005|-0.012|-0.005|-0.012|
||(0.011)|(0.015)|(0.011)|(0.015)|
|Constant|0.292***|0.389***|0.288***|0.387***|

20
# 1. Introduction

Growth theory has for long established that improvements in technology have an effect on long-run growth (Romer, 1990; Aghion and Howitt, 1998). Moreover, differences in technology have been found to be an important determinant of differences in total factor productivity across countries (Hall and Jones, 1999; Klenow and Rodriguez-Clare, 1997) and across fi rms (Griliches, 1998; Parisi et al., 2006). While most fi rms improve their technology by simply imitating or adapting existing production techniques to local conditions, other fi rms are truly engaged in the creation of new technologies. Even though this is true for fi rms worldwide, this is particularly important in developing countries. There, the adoption of existing technologies from abroad can occur through the contacts with foreign partners, foreign suppliers and/or foreign clients or through the direct trade in technologies (e.g., licensing). Most empirical studies on the international diffusion of knowledge provide indirect evidence on the importance of different channels by documenting a link between trade or FDI and fi rm-level productivity. In this paper, we use fi rm-level data on the adoption of new technology in several developing countries to provide new evidence on the incentives of fi rms to adopt new technology and on the importance that trade and foreign direct investment (FDI) have as channels for the diffusion of technology.<sup>1</sup> New technologies can be transmitted across countries through different activities. Foreign direct investment is one possible channel. Multinational parents, endowed with a more advanced technology, usually transfer their knowledge and technology to their subsidiaries. However, there is some debate on the quality of the technology that is actually transferred from multinational parents. Throughout the world, many policies to attract FDI are based on the premise that joint ventures between foreign and domestic-owned fi rms are more fruitful than fully-owned foreign subsidiaries because they induce a greater technology transfer. This view is not consensual, though, as there is some evidence that multinational parents

> 1The international diffusion of technology to fi rms integrated into global markets may subsequently spill over to other domestic fi rms in the same region or industry not directly engaged in international activities. The latter could happen through demonstration effects, labor turnover, or reverse engineering. This paper will focus only on technology transfers to fi rms integrated into global markets, not on spillovers.

2
16 resulted in a major upgrading of its accounting framework,<sup>includingtheintroductionof</sup> forward-looking loan classification and provisioning norms. Thailand<sup>significantly upgradedits</sup> classification and provisioning requirements and somewhat<sup>tightenedinterestaccrualrulesin</sup> 1999 bringing the overall accounting framework much closer<sup>to international best practice.Yet,</sup> immediate loan reclassification for restructured debt was<sup>allowed,freeingup previously made</sup> provisions after a debt workout (World Bank 2000b).

**Table 5. Comparison of the Restructuring Framework for**<sup>**Banks**</sup> **and of the** Financial **Results for the Corporate Sector** (at the onset of the crisis (in brackets) and five years into the crisis)

|||Frame|work fordecen|tralizedrestru|cturing||Result|
|---|---|---|---|---|---|---|---|
|Country|Bank<br>capital<br>positions|Accounting<br>framework|Efficiency<br>and<br>enforcement|Ownership<br>structure|Overall<br>index|Improvement<br>inoverall<br>index|Financial<br>conditionof<br>corporate sector|
|Argentina<br>(1980-82)|(1)1|(1.0)1.0|(0.6)0.6|(2)2|(1.2)1.2|+0.0|(1)1|
|Chile<br>(1981-86)|(1) 3|(2.5) 3.7|(0.7)0.7|(1) 3|(1.5)2.8|+1.3|(2)3|
|Hungary<br>(1991-95)|(1) 1|(2.5)3.0|(0.6)0.7|(1) 3|(1.3)1.9|+0.6|(1)2|
|Japan<br>(1991-<br>ongoing)|(2) 2|(2.0)2.0|(1.6)1.6|(3)3|(2.2) 2.2|+0.0|(2)2|
|Norway<br>(1987-93)|(3)4|(3.7)4.0|(2.0)2.0|(3) 3|(2.9)3.3|+0.4|(3)4|
|Poland<br>(1992-95)|(1)3|(3.2) 3.3|(0.6)0.7|(1)3|(1.5)2.5|+1.0|(1) 3|
|Thailand<br>(1997-|(1)2|(1.0)2.7|(0.9)0.9<br>|(1) 1<br> <br>|(1.0)1.7<br>|+0.7<br>|(2)2<br>|
|ongoing)<br> <br>**_So_**<br>for|_<br>__<br>_<br>**_urce:_**Tables2-4;<br>Reconstructionan|_<br> Borish,Dingand <br>dDevelopment19|I<br>Noel 1996;Claessens<br>98;KanayaandWoo|_<br> <br> <sup>2001;Claessaens, </sup><br> 2000;<sup>Karlsen2000</sup>|_I<br><sup>Djankovand Klin</sup><br><sup>;Sheng1996c;</sup>|_<br>-_I_<br><sup>gebiel1999a and1999</sup><br> <sup>WorldBank1985;W </sup>|I<br><sup>b;European Bank</sup><br><sup>orldBank2000b.</sup>|

**_c Improving the legal framework._** None of the countries in our<sup>samplemadesignificant</sup> changes to their formal balnkruptcy regime and therefore a number of weaknesses<sup>in theformal</sup> bankruptcy law were not eliminated (see fourth column Table 5).

However, four out of seven countries complemented their<sup>formalframeworkfor</sup> reorganization and debt workouts with out-of-court extra-judicial procedures<sup>toaccelerate</sup> restructuring. In the 1980s, Chile used private arbitration to resolve liquidations<sup>and</sup> bankruptcies as an altemative to the outdated and slow judiciary<sup>system(Barandiaranand Luders</sup> 2000). In the absence of fully developed liquidation and<sup>bankruptcylegislationaswellasa</sup> skilled and efficient court system, Poland launched its well<sup>knownprogramofbankand</sup>
Table 5: Most Traded Product Categories

|**Rank**|**HS Chap**|**Volume**|**Sublines**|
|---|---|---|---|
|1)|85|72016273408|1143|
|2)|84|56461922304|1571|
|3)|62|43022950400|691|
|4)|95|28904214528|201|
|5)|64|23138717696|155|
|6)|42|22812508160|133|
|7)|61|22808842240|546|
|8)|71|15531491328|197|
|9)|94|14395513856|201|
|10)|39|13629872128|455|
|11)|90|12428760064|564|
|12)|29|9915683840|614|
|13)|26|9161824256|33|
|14)|73|8236248064|419|
|15)|63|7497201152|264|
|16)|27|6954802688|62|
|Total||468719960064||

Notes: Breakdown of most traded product categories in terms of HS 2-digit chapters. Trade volumes in column 3 are pooled over countries and years. Column 4 indicates richness of product variety by listing the number of tariff lines below the HS 2-digit level in any given category.

28
Mincer, J., 1974. “Schooling, Experience and Earnings”, NBER Working Paper, New York.

- Murmis, Miguel, 1996. “Pobreza rural y ocupación: revisión de algunos datos inéditos”. In Revista estudios del trabajo N 12.

- Mwabu, Germano and T. Paul, Schultz, 1996, “Education Returns Across Quantiles of the Wage Function: Alternative Explanations for Returns to Education by Race in South Africa”, American Economic Review, vol. 86 (2), pp. 335-339.

- Neiman, Guillermo, 2000. “Crecimiento y exclusión. Nuevas y viejas formas de pobreza rural en Argentina”. In Pobres, pobreza y Exclusión social. CEIL 2000.

- ______, 2003. “Los salarios de los trabajadores comprendidos en el regimen nacional de trabajo agrario” ILO.

- Nussbaumer, Beatriz, 2004. “Toward Millennium Development Goals: Migration and Poverty Reproduction in rural Places. Cases of the Chaco Region in Argentina.”

Oxford Analytica; http://www.oxweb.com.

PRODERNOA, 2003. “Estudio de base PRODERNOA, provincia de Catamarca. Mimeo.

PROINDER, 2005. Information provided by the Coordination Unit. ______ , 2003. “Estudio de base PRODERNOA”, provincia de Formosa. Mimeo.

- Schiovani, Lidia, 2000. “Aportes de hijas e hijos a las estrategias de vida familiar. Familias pobres urbanas y rurales en la provincia de Misiones”.

- Taylor, J. E. and A. Yuwez-Naude, 2000. "The Returns From Schooling In A Diversified Rural Economy", American Journal of Agriculture Econ. 82, May. pp. 287-297.

- Verner, Dorte, 2004. “Rural Poverty in Mexico During 1992-2002”, The World Bank, Washington, DC. Mimeo.

- Verner, Dorte, 2006. “Labor Markets and Income Generation in Rural Argentina”, The World Bank, Washington, DC. Mimeo.

University of La Plata, 2004: web page (http:// <u>www.depeco.econo.unlp.edu.ar.</u> Wiens, Tom, 1998. “Rural Poverty in Argentina”, World Bank :Washington, DC.

- World Bank, 2004 “Rural Infrastructure in Argentina:  Its Challenges, Key Issues and Options for its Development” Report No. 26271. World Bank :Washington, DC.

52
34 The age of political parties is correlated with national income. It is possible that the significant interaction of party age and elections is influenced by this correlation. To examine this, we repeated the specifications in columns 1 – 4 in Table 4, substituting the interaction between log income per capita and the election year dummy for the democratic age-election year interaction. Using either the original Brender-Drazen sample or our base sample, income has no effect on political budget cycles: the coefficient on the income-election year interaction is entirely insignificant. In contrast, the party ageelection year interaction retains both its magnitude and significance, under either sample, in the presence of the income-election year interaction. Table 5 displays a summary of the two significant results.

**Table 5: Robustness checks:  Party age or income per capita?**

|DV: Centralgovt. total expend.|B&D sample|Base sample|
|---|---|---|
||0.283|0.675**|
|Election|(1.52)|(0.286)|
||**0.046**|**-.006**|
|**Log GDP/capita X Election**|**(0.17)**|**(0.112)**|
||0.003|-0.002|
|Avg. party age|(0.008)|(0.006)|
||**-0.011*****|**-0.009****|
|**Avg. party age X Election**|**(0.004)**|**(0.004)**|
||0.904***|0.929***|
|Lagged dependent variable|(0.026)|(0.023)|
||0.76|0.581***|
|Log GDP per capita|(0.48)|(0.199)|
||-0.268**|-0.120***|
|Output gap (Growth)|(0.115)|(0.031)|
||-0.519|0.126|
|Ruling coalition size|(0.925)|(0.856)|
||0.729|1.022***|
|Unifiedgovernment|(0.489)|(0.317)|
|Time dummies|Yes|Yes|
|AR (1)|-4.14***|-4.26***|
|AR (2)|1.18|0.38|
|Number of observations|998|1,128|
|Number of countries|65|65|

*** p<0.01, ** p<0.05, * p<0.1.  Constant not reported.
1984 and 1985; it dropped to 7% in 1986, then increased to 15% in 1987, and dropped again to 10% and 9% in 1988 and 1989.

# **III Hypotheses about the Determinants of Decentralization**

Using a principal-agent (PA) approach, this section discusses what determines the way the government and SOEs decide internal and managerial incentives, financing arrangements, and control rights over production decisions. Consider this PA relationship: the government as the principal is risk-neutral, and the manager of a SOE as the agent is risk averse. For some reforms, I shall also consider a PA relationship between the manager as the principal and his employees as his agents. The government is postulated to have three goals: increase revenue (or profitability), retain control of SOEs which represent high control amenity -- that is, utility from directly controlling the firms - - to the government, and reduce the inequality of income across firms. Managers and employees have an informational advantage over the government that allows them to earn a rent, and that advantage, as a result, causes sub-optimal effort and investment levels. To reduce the informational asymmetry, the government can design managerial and employee incentives, control rights and performance contracts to align the objectives of **13** the SOEs with those of the government. The manager, of course, may opt for the more centralized status quo if the firm is better off than under the considered reform.

# _Incentives, Control and Risks_

In designing incentives the government would like to differentiate between firms in terms of the risks they face, and strike a balance between incentives and insurance.14 In

> **13** See Laffont and Tirole (1993), chapter 1, _A Theory of Incentives in Procurement and Regulation,_ the MIT Press: Cambridge, Massachusetts.

**14For** surveys on principal-agent models, see David Sappington, "Incentives in Principal-Agent Relationships," _Journal of Economic Perspectives, 5(2),_ 1991, p. 45-66; Bengt Holmstrom and Jean Tirole, "The Theory of the Firm," in Schmalensee R., and R. Willig eds., _Handbook of Industrial Organization,_ Amsterdam: North-Holland, 1989.

8
# **Table 2**

Investor-Only Momentum at the Fund Level

||**AllSample**|**Non-Crisis**|**Crisis**|
|---|---|---|---|
|**Investor-Only:FundLee**||||
|**LOM**|**1.99*****|**0.97*****|**3.78*****|
|T-statistic|_5.49_|**3.55**|**4.30**|
|Observations|**127**|**81**|46|
|LIM|0,54***|0.49*|**0.63****|
|T-statistic|**2.83**|**1.79**|**2.09**|
|Observations|**_115_**|**72**|43|

LOM is the point estimate for the mean lag-0 momentum trading measure. LIM is the point estimate for **the** mean lag-I momentum trading measure (measured from return over the previous month). Investor-Only: Fund Level reflects only investor redemption effects at the fund level as in equation (4). **All** t-statistics are corrected for heteroskedasticity across funds. Full sample: quarterly data from April **1993** to January **1999.** The crisis portion of the sample is December 1994-June **1995,** July 1997-March **1998,** August 1998-October **1998,** and January **1999.** The non-crisis portion is the rest of the sample. The total of roughly **127** observations is **13** funds times an average of about **10** quarters of available data per fund For robustness, results in each cell are based only on observations within three standard deviations of the mean.

> Statistically Significant at the 10-percent level

> ** Statistically Significant at the 5-percent level

** Statistically Significant at the I-percent level

**27**
Figure 6. Cumulative Distribution Function of Volatility of Import Quantities <!-- Start of picture text --> 1<br>0.9<br>0.8<br>0.7<br>0.6<br>0.5<br>0.4<br>0.3<br>0.2<br>0.1<br>0<br>0 1 2 3<br>standard deviations<br>primary commodities all manufactured goods<br>cumulative distribution functions<br><!-- End of picture text --> Note: The figure shows the cumulative distribution functions of the standard deviations of HodrickPrescott filtered series of individual goods quantities. Data are from the Foreign Trade Division of the U.S. Census Bureau.

22
**Table S9: Treatment Effect Estimates Using Baseline Variables as Outcomes (Visits)**

||Any Provider|Pharmacy|EMP|Public Facilities|Private Facilities|
|---|---|---|---|---|---|
|Panel A: Ever Visit|(1)|(2)|(3)|(4)|(5)|
|Parent Enrolled|-0.011|0.020|-0.037|0.043|0.010|
||(0.014)|(0.055)|(0.033)|(0.073)|(0.075)|
|Parent Enrolled*Ineligible|-0.004|-0.057|0.076**|-0.074|0.025|
||(0.024)|(0.087)|(0.037)|(0.125)|(0.123)|
|Ineligible|-0.002|0.010|-0.014|0.040|-0.008|
||(0.007)|(0.028)|(0.013)|(0.040)|(0.039)|
|Observations|2996|2996|2996|2996|2996|
|R-squared|0.957|0.599|0.015|0.184|0.197|
|P-value of Enrolled + Enrolled*Ineligible|0.503|0.626|0.044|0.782|0.752|
|Panel B: Number of Visits|(1)|(2)|(3)|(4)|(5)|
|Parent Enrolled|-0.716|-0.044|-0.068|0.011|-0.663|
||(0.837)|(0.354)|(0.198)|(0.301)|(0.489)|
|Parent Enrolled*Ineligible|0.815|-0.300|0.175|0.231|0.860|
||(1.156)|(0.517)|(0.183)|(0.416)|(0.660)|
|Ineligible|0.067|0.207|-0.034|0.093|-0.343|
||(0.463)|(0.183)|(0.082)|(0.129)|(0.302)|
|Observations|2996|2996|2996|2996|2996|
|R-squared|0.205|0.216|0.021|0.12|0.051|
|P-value of Enrolled + Enrolled*Ineligible|0.918|0.437|0.077|0.499|0.687|

_Notes:_ The sample is all children aged 15 and under (N=2996). Children age 12-15 are considered "Ineligible" and children under 11 are considered "Eligible". Above regressions are estimated coefficients from IV estimates where "Parent Enrolled" is instrumented with the parent's random assignment status and Parent Enrolled*Ineligible is the interaction of these two variables. The dependent variable in Panel A is whether or not the child has visited various providers over the past year as of baseline. The dependent variable in Panel B is the number of times the child has visited various providers over the past year. Regressions control for baseline measures of household size, household size squared, the inverse hyperbolic sine of household income, parent's years of education, age of child, age of child squared, gender, whether the child was sick in the past year, the number of times sick, total number of health visits, and survey round and market fixed effects. Individuals without valid income data were imputed to be the median and regressions were run with a dummy variable indicating the missing value. Robust standard errors in parentheses, clustered at the family level. *** p<0.01, ** p<0.05, * p<0.1 _Source:_ Authors’ analysis based on data described in paper.

9
establishing shorter statutory deadlines for reorganization plans, reducing opportunities for appeal by debtors and requiring mandatory liquidation in cases of failed negotiations.

We present a simple model that describes the decision to reorganize or liquidate a financially distressed firm as a function of reorganization costs. In a regime with high idiosyncratic reorganization costs, some viable businesses may be liquidated if the costs they face are too high. In this case, the bankruptcy system fails to separate viable from unviable firms, resulting in inefficient outcomes. In contrast, when reorganization costs are low, the model predicts that better quality firms are more likely to choose reorganization, resulting in a clear separation between firms that reorganize and those that liquidate. In this regime, as a result of both lower costs and better selection, the recovery after reorganization is significantly improved thus contributing to more efficient outcomes. The Colombian reform can be seen as a natural experiment with two regimes that match our model – a pre-reform regime with high reorganization costs and the postreform regime with low costs.

We use a unique dataset obtained from the Colombian Superintendence of Companies which includes a total of 1,924 bankruptcy cases, representing the _universe_ of cases filed between 1996 and 2004, conveniently spanning the reform episode. We also use data of about 14,000 active companies that report to the same Superintendence over the same time period. One attractive feature of the dataset is that it predominantly consists of non-listed firms thus complementing the US literature, which has focused mainly on public firms.<sup>2</sup> The financial data we use come only from financial statements, and so we rely on accounting-based models (e.g. Z-score model of Altman 1968 and 2000) to construct an indicator of financial distress.

We show that the reform achieved a reduction in reorganization costs that made reorganization an attractive option for distressed but viable firms. First, we find that the duration of reorganization proceedings significantly decreases overall and also relative to the duration of liquidations with the new reorganization code. This finding supports our

> 2 The literature on reorganization costs in the US mostly draws conclusions from the relatively small number of public corporations (see for example Altman, 1984; Weiss, 1990 and Weiss and Wruck, 1998). A notable exception is Bris et al. (2005), which use a sample of 286 public and private firms, the largest sample in the US, and Davydenko and Franks (2005) who use a large sample of small firms from France, Germany and the UK.

3