rafmacalaba/datause-encoder-data huggingface dataset:
production costs for the private sector and stimulate investment, but also improve education and health outcomes, by making it easier for individuals to attend school and seek health care. With their health improving, individuals become not only more productive, but they also tend to study more. In turn, a higher level of education makes individuals more aware of potential risks to their own health and that of their family members. Moreover, investment in infrastructure, by improving health and life expectancy, may reduce uncertainty about longevity and the risk of death, thereby increasing the propensity to save. As a result of these various effects, the impact of infrastructure on growth is compounded.

# **IV.  Implications for Growth and Public Spending Allocation**

The foregoing analysis suggests that it is crucial, in designing growthpromoting strategies, to account for the variety of channels, direct and indirect, through which infrastructure affects the economy. This is important because the complementarities that appear at the micro level among infrastructure, health, and education (as discussed earlier) may give way to potential trade-offs at the macro level. The reason is that the provision of any type of services requires the use of (limited) public resources. Understanding the nature of these trade-offs is essential for determining the composition of public spending in a growth context.

To illustrate the issues involved, this section examines the optimal allocation of government spending between health and infrastructure in an endogenous growth framework where public capital is an input in the production of final goods as well as the production of health services<sup>16</sup> . Put differently, what matters to produce health services is not only spending on health _per se_ , but the combination of public spending on health and infrastructure. As noted earlier, to function properly, hospitals need access to electricity. With inadequate water, sanitation, and waste disposal

> 15In a study based on a large sample of industrial and developing countries over the period 1850 to 1990, Tamura (2006) found that higher levels of human capital (as measured by the number of years of schooling of the average 25-year old) tend also to lower the mortality rate of young adults. 16Barro (1990) was one of the first to propose a formal analysis of the link between public infrastructure and growth. See Zagler and Durnecker (2003) for an overview of some of the literature spawn by Barro’s contribution. Our focus here is on the links between infrastructure and health.

25
## WPS4019

# **Banking Sector Openness**

# **and Economic Growth**

Nihal Bayraktar and Yan Wang*

### **Abstract**

Banking sector openness may directly affect growth by improving the access to financial services and indirectly by improving the efficiency of financial intermediaries, both of which reduce the cost of financing, and in turn, stimulate capital accumulation and economic growth. The objective of the paper is to empirically reinvestigate these direct and indirect links, using a more advanced econometric technique (GMM dynamic panel estimators). An illustrative model is presented to link financial market development with investment. The empirical results confirm the presence of direct and indirect links, and thus provide support for countries planning to open their banking sector for international competition.

JEL Classification: G21; O16; O40; F10; F21.

Key words : Banking sector openness; foreign banks; efficiency of banks; economic growth; capital accumulation.

World Bank Policy Research Working Paper 4019, October 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._ ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯

* Respectively, Penn State University-Harrisburg and the World Bank. This is part of a larger effort in WBIPR-Trade to develop materials for capacity building on trade in financial services. The authors thank Stijn Claessens, Roumeen Islam, Will Martin, Aaditya Mattoo, Gianni Zanini and trade team for encouragement and comments.

1
individual contributions.

Table 16 Proportion of men and women in each decile of distribution on basis of own and of joint contributions

||1st|2nd|3rd|4th|5th|6th|7th|8th|9th|Top|
|---|---|---|---|---|---|---|---|---|---|---|
|M Own|0.9|0.8|3.8|5.4|10.9|12.6|13.3|16.1|17.8|18.4|
|Jnt|5.2|8.1|9.6|10.7|10.7|9.8|11.7|10.5|11.2|12.7|
|F<br>Own|18.1|18.3|15.5|14.2|9.1|7.7|7.1|4.5|3.1|2.4|
|Jnt<br>-|14.3<br>~-|11.7<br>.|10.4|9.4|9.3|10.2|8.5|9.5|9.0|7.6|

# Capital top-ups

With joint contributions over one third of men and more than half of women still fail to accumulate a fund capable of purchasing a pension annuity at age 65 equal to 33% of average full-time male earnings. If a funded pension system is to satisfy the criterion of poverty prevention, then these individuals will need a tax transfer in order to obtain a minimum pension. We have modelled the cost of providing lumpsum capital top-ups to people who reach age 65 with a pension fund less than the amount required for a 33% replacement rate.

Table 17 shows the mean amount of lump-sum top-up for individual and joint contributions, for the entire LIFEMOD population, and for men and women separately. Not surprisingly, given what has already been said about women's earnings, it is women who receive the majority of the capital top-ups - alrr cst 90% on the basis of individual contributions, and two-thirds of top-ups on the basis of joint contributions. As noted above, the joint contribution rule reduces the proportion of men who reach the 33% replacement threshold, and so increases the proportion receiving lump-sum capital top-ups.

56
# **1. Introduction**

While many economists tend to focus on the structure of output, little attention is usually paid to the importance of changing the structure of employment. In the particular context of African economies, relative shifts in production – from agriculture to industry and services – have rarely been followed by commensurate changes in sectoral employment. This undermines the impact and sustainability of the growth process, since research has shown that structural change (in the labor market) is vital for sustaining economic and social development.

In this paper, we conduct an investigation of the structural changes that have taken place in Ethiopia over the past 15 years. For that purpose, we use macroeconomic and household survey data disaggregated into eight sectors to answer the following key questions:

- How has the sectoral composition of output and employment changed over time?

- What are the trends in labor productivity?

- What have been the relative contributions of within-sector productivity and structural change (i.e. labor shifting from low- to high-productivity sectors) to output per capita growth?

Our results suggest that the structure of output has changed considerably. For instance, the share of agriculture in total output declined from 66 percent in 1991 to 45 percent in 2011, while the services have expanded considerably – especially commerce and real estate activities. However, changes in the composition of employment have lagged behind. The share of agricultural employment in total employment remains very high, at about 78 percent. Nonetheless, labor productivity growth has been strong across most sectors (including agriculture), with total output per worker doubling in the past decade. This performance has been mainly driven by within-sector productivity improvements, although the relative contribution of structural change is increasing.

This paper is structured as follows. Section 2 provides a brief overview of the literature on structural change. Section 3 assesses trends in the level, growth and composition of output (value added) and employment, as well as sectoral productivity and employment elasticities by economic sector. In section 4 we use suitable analytical tools to decompose labor productivity growth into within-sector and between-sector changes, while also taking into consideration demographic effects. Section 5 concludes.

4
# **Table 6.  Vulnerability by Firm Size (Sales) in 2006**

||First Quartile<br>(smallest)|Second<br>Quartile|Third Quartile|Fourth Quarti<br>(Largest)|le<br>All|
|---|---|---|---|---|---|
|ROA|-1.6%|1.8%|3.2%|7.3%|2.7%|
|Quick Ratio|6.4|4.7|2.5|1.5|3.8|
|Current Liabilities to Total||||||
|Liabilities|82%|89%|83%|78%|83%|
|Total Liabilities to Total<br>Assets|24%|26%|32%|40%|30%|
|Total Debt (estimated)||||||
|Over Total Assets|19%|19%|25%|31%|23%|
|Interest Coverage|3.3|6.6|8.9|23.9|11.5|
|Interest Coverage Less||||||
|than 0.75|28%|23%|20%|10%|20%|
|Uncovered Debt Ratio||||||
|(Interest Coverage < .75)|38%|30%|7%|9%|21%|
|Altman Z-score|6.6|5.8|4.6|5.2|5.4|
|NumberofObservations*|39|39|40|40|158|

# **3.4 Key Measures of Corporate Vulnerability**

This section describes two key measures that will be used below in corporate stress testing and bank stress testing.

The proportion of firms in the industry that find it difficult to meet their interest payments with current earnings, i.e. for which interest coverage ratio falls below a certain threshold (such as below 1, or below 0.75) is one metric of sectoral level vulnerability. The higher proportion of firms in the industry that find it difficult to meet their interest payment, the more vulnerable that industry is, and the higher risk the banks with higher exposure to that industry will bear.

Table 7 reports proportion of firms with interest coverage below 0.75 by sector in 2006 (the latest year with corporate data) along with the number of firms in each sector. (Table 7 simply replicates several rows from Table 3 above). The transportation sector has the largest proportion of firms with industry coverage below 0.75: 30% of all firms, followed by industry, 27%, services and construction at 22%.

16
benefits, irrespective of the poverty or the marginal productivity criterion for program participation. The authors find the occurrence of elite capture to be pronounced in villages with more unequal land distributions and that are further away from the rural towns.

Given the massive scale of the FISP and its variety of documented and potential impacts at the macro, meso, and micro levels, including on agricultural production, food security/food selfsufficiency, welfare, displacement of unsubsidized fertilizer purchases, food prices and casual labor wage rates, beneficiary targeting is a central piece in the program design. With the literature on decentralization in mind, we now turn to the country context and the description of the program.

# **3 COUNTRY CONTEXT**

Malawi is one of the poorest countries in the world, ranking 170 of 186 in terms of the 2012 United Nations Human Development Index values. Eighty-five percent of its population resides in rural areas (Malawi NSO, 2012) and agriculture is not only the backbone of Malawi’s economy, but also an essential part of its social fabric. The sector accounts for 30 percent of the gross domestic product (GDP) and 84 percent of all Malawian households own and/or cultivate land<sup>4</sup> . The production system is overwhelmingly rainfed, characterized by limited access to irrigation and diminishing average landholding sizes due to population pressures. The rainfall is unimodal; maize is the main staple crop, grown by nearly 100 percent of the farming household population; and maize availability typically defines the food security status of the country.<sup>5</sup> The majority of the farming households still practice subsistence agriculture: the rates of market participation among farming households in general and maize-producing households in particular are 42 and 15 percent, respectively.<sup>6</sup> Over time, the government has adopted a range of strategies to promote the agricultural sector. Policies in the 1960s and 1970s were geared toward promotion of large-scale estate farming via a state-run input and output intermediary (Chibwana et al. 2010). Following reforms undertaken via a structural adjustment program (SAP) and at the directive of the World Bank, the government turned away from estate-oriented policies and toward small-scale farming policies (Chibwana et al. 2010). Over the last two decades, however, agricultural productivity, as measured by maize yields (kilogram/hectare), has been erratic, as shown in Figure 1. The factors that are commonly cited as underlying the agricultural productivity trend include weather variability, declining soil fertility, limited use of improved agricultural technologies and sustainable land management practices, rationed agricultural extension services, market failures,

> 4 The GDP contribution of agriculture is for 2011. The estimate of the percentage of Malawian households owning and/or cultivating land is based on the Third Integrated Household Survey (IHS3) 2010/11 data. 5 The estimate is based on the IHS3 data.

> 6 The estimate is based on the IHS3 data.

7
22 RENT CONTROL IN KUMASI, GHANA industries. Most (80 percent) of BHC's current lending is for the construction industry although, as will be seen in the discussion of the housing fund below, BHC may take on more responsibilities for end user and other housing finance in the fut-ire, Among other issues which would have to be addressed for BHC in particular as well as the system in general are the improving mortgage origination and servicing, new instruments, improving the resource mobilization side of housing finance, the need to separate commercial and development banking functions, and ways to improve appraisal practices.

First Ghana Building Society. FGBS dates from 1956. Formed in response to a U.N. mission's recommendation about the need for a specialized housing finance 'nstitution, FGBS is currently almost moribund. Negative real interest rates ensure that deposits are not a significant proportion of the sources of funds for FGBS. Government provides the bulk of capital (recently about C217 million). A total of only 779 loans are presently outstanding, valued at C143 million. While detailed records were not readily available, it appears that as few as four loans have been made in some past years, and by any measure few loans are currently being made.

Depositors are paid 6-9 percent (compared to commercial banks which pay 15 percent). Loans are at variable rates (presently 20 percent). Loan terms vary between 1-30 years depending on the age of the person (FGBS's policy is that loans should be amortized before the borrower reaches retirement age). A maximum loan of C500,000 is allowed up to a maximum of 80% of building value. Generally, payments records on loans are reportedly good and there have been no recent foreclosures. But in the current macroeconomic environment FGBS is obviously and severely constrained by their deposit and lending policies.

Social Security and National Insurance Trust. SSNIT is a provident fund which is currently in the process of converting to a pension scheme.3<sup>1</sup> Begun in 1965, the Trust's status as a provident fund was always meant as a temporary expedient, but conversion was delayed by political issues. However, given the fixed defined benefits and high recent inflation, the value of provident fund

- L/ Briefly, a provident fund is a mandatory savings scheme for workers which pays a lump sum distribution under certain predefined conditions. A pension fund pays out periodically, based on actuarial estimates of a participant's expected lifetime. Either kind of system can be funded actuarially, or pay-as-you-go. When participation is mandatory, any of these systems can be analyzed as a tax, although the degree of implicit taxation depends on the way the benefit is defined and calculated. Detailed discussions are beyond the scope of this report; see Wallich (1983) for more details. For more information about the Ghanaian system and proposals for change, see SSNIT (1987).
with output per worker demeaned by the country average to assess whether the impact of bribes on policy implementation times varies with firm productivity (perhaps because they are more willing to pay). Although the estimated interaction effect is positive, it is not statistically significant; the null hypothesis that more productive firms are not able to get things done faster cannot be rejected.

# <TABLE 8 HERE>

Second, interactions between firm size and bribe requests are included in the specification presented in column 2. Larger firms suffer longer delays when confronted with demands for bribes, since the interaction between bribe incidence and firm size and its square are jointly statistically significant. One possible explanation for this finding is that their projects are characterized by greater complexity and hence longer wait times.<sup>16</sup> Third, by including a proxy for the share of profits firms perceive other firms to pay in bribes on an annual basis, we assess whether the relationship between demand for bribes and implementation times varies with the likely magnitude of bribe payments. The results are robust to controlling for this proxy for the severity of corruption, and, moreover, the interaction term between the bribe-amount and bribe incidence is not statistically significant. Thus, these results do not support the prediction of the “grease” hypothesis that corruption accelerates implementation for firms with a higher willingness to pay.

Fourth, we assess the relationship between de facto policy implementation times reported in the Enterprise Surveys and de jure time it should take to get these things done as proxied by the Doing Business indicators. Specifically, we create a dummy indicating whether a country has burdensome regulation, defined here as in countries in which it takes at least 200 days to get a

> 16 This finding further reinforces the importance of the robustness check of including firm level fixed effects that should help control for the complexity of the projects firms undertake.

23
Figure 3.6. Sensitivity analysis: Initial rural-urban service and cost gaps.

<!-- Start of picture text --> 27<br>24<br>21<br>Central case<br>18<br>15<br>Large urban-rural<br>12 service gap<br>9 Small urban-rural<br>service gap<br>6<br>Large rural-urban<br>3<br>cost gap<br>0<br>0 1 2 3 4 5 6<br>Health service efficiency growth (% per year)<br>(US$2009 per capita)<br>Grant increase in average year<br><!-- End of picture text -->

# 4. CONCLUDING OBSERVATIONS

This paper projects the evolution of an archetypical LIC up to 2030, covering not only standard economic indicators but also human development indicators, including a set of MDGs with a rural-urban disaggregation. The results indicate that, for the “business-as-usual” _base_ scenario, considerable progress is realized, including a substantial narrowing of rural-urban MDG gaps.

The policy simulations explore the consequences of increased provision of government health services to the rural population with the aim of closing gaps in terms of per-capita services or the U5MR. The results indicate that, if the government, by mobilizing required resources and/or by raising its own efficiency in the health sector, manages to raise the level of real health services reaching the rural population, then it is possible to considerably reduce the rural U5MR. If the bulk of resources come in the form of foreign grants or cost-reducing efficiency gains, then progress in the form of a lower U5MR can come with positive repercussions for other key development indicators, including poverty reduction. However, if most additional resources are mobilized from domestic sources, then this progress would threaten to come at the expense of less progress in terms of other indicators, illustrating the difficult tradeoffs faced by LICs and their governments.

# REFERENCES

Annabi, Nabil, John Cockburn, and Bernard Decaluwé (2006). Functional Forms and Parametrization of CGE Models. MPIA Working Paper 2006-04. Poverty and Economic Policy (PEP) Network (downloadable from www.pep-net.org).

19
**Table 2: Explaining levels of urbanization**

|Regression<br>Dates available|1<br>1965-95|2<br>1965-95|3<br>1965-95|4<br>1965-90|_5_<br>1965-90|6<br>1970-95|7<br>1965-95|8<br>1965-95|9<br>1965-90|10<br>1980-95|I1<br>1965-90|
|---|---|---|---|---|---|---|---|---|---|---|---|
|Ln(Y)|1.46**|1.46**|1.73**|1.78**|1.91**|1.73**|1.79**|1.71**|1.80**|1.66**|2.06**|
|<br>(Ln(y))<br>2|-0.080**|-0.080**|-0.095**|-0.10**|-0.11**|-0.096**|-0.10**|-0.095**|-0.10**|-0.090**|-0.12**|
|<br>Ln (Yag/Y)|-0.13**|-0.13**|-0.13**|-0.22**|-0.12**|-0.14**|-0.16**|-0.15**|-0.22**|-0.10**|-0.18**|
|<br>Ln(Ymanuf/Y)<br>Year|0.13**<br>0.013**|0.10**<br>0.013**|0.11**<br>0.013**|0.12**|0.15**<br>0.0048|0.099**|0.12**|0.12**<br>0|0.11**|0.0084|0.19**|
|Africa|-0.028|||||||||||
|Africa*pre8O||-0.19**|0.27|0.14|1.30**|0.44|0.28|0.21|0.22|0.677|1.29**|
|Africa*post8O||0.12**|1.66**|1.54**|2.01**|1.61**|L95**|1.74**|1.61**|1.46**|2.28**|
|<br>Africa*pre80*1n(Y)|||-0.067|-0.031|-0.20**|-0.091 *|-0.069|-0.062|-0.041|-0.12*|-0.19**|
|<br>Africa*pre80*1n(Y)|<br>||-0.24**|-0.21**|-0.29**|-0.23**|-0.28**|-0.25**|-0.22**|-0.21**|-0.32**|
|post80|-0.031|-0.12**|-0.12**||-0.061|||||||
|Ln(Ruw)||||0.18**|||||0.17**||0.15**|
|Ln(Noeduc)|||||-0.14**||||||-0.17**|
|<br>(Ln(Noeduc))<sup>2</sup>|||||0.046**||||||0.055**|
|Ln(secondary)|||||0.18**||||||0.14**|
|<br>Cereal||||||0.033**||||||
|BMP|||||||0.00016**|||||
|Poscropsh||||||||0.0049||||
|Negcropsh||||||||-0.0022||||
|<br>Sivard|||||||||0.076**|0.076*|0.057*|
|Ln(foodaidc)<br>Ln(foodaidnc)||||||||||-0.031*<br>0.084**||
|Adj. R<sup>2</sup>|.801|.813|.826|.855|.875|.822|.822|.816|.856|.802|.879|
|N|494|494|494|398|352|437|450|494|398|331|346|

The dependant variable is the log of the level of urbanization defined as (urban population/total population). Note: * (**) indicate significance at the 5% (10%) level. The sample is an unbalanced panel consisting of up to 100 countries every 5 years between 1965 and 1995. Results are robust to heteroscedasticity using White's method.