rafmacalaba/datause-encoder-data huggingface dataset:
in Tunisia (this is the case for fuel, for which subsidies in Libya cover 80% of the cost) or are much more heavily taxed in Tunisia than in Libya (all the other products listed above), leading to significant differences in price (see Table 2).

**Table 2: Price of various goods in Tunisia and Libya**

|Product|Unit|Tunisian price<br>(in TND)|Libyan price<br>(in TND equivalent)|
|---|---|---|---|
|Cheese (gruyère)|kg|30|15|
|Corn oil|1 liter|3|1.2|
|Bananas|kg|3|1.5|
|Gasoline|1 liter|1.57|0.19|
|Fuel oil|1 liter|1.17|0.19|
|Air conditioners|12,000 BTU|900|560|

Data source : surveys.

# **Tables 3 and 4 highlight the burden of taxes levied on imports from Libya to Tunisia for the above-**

**mentioned products** . The tariffs are the MFN (Most Favored Nation) rates levied by Tunisia on all its trading partners in line with its World Trade Organization (WTO) commitments. As Libya is not a member of the WTO, since 2005, it has been imposing a unilateral levy of 5.25% on almost all of its tariff lines. These rates are not the same as those applied under regional trading agreements such as the Euro-Mediterranean Free Trade Area (EuroMed) or the Greater Arab Free Trade Area (Gafta), which cover manufactured products. Rates applied under the terms of these agreements are more advantageous and are often virtually zero.

12
Table 5: Probability of birth as a function of ultrasound availability and firstborn sex

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
|_Firstborn girl_|0.0352***|0.0357***|0.0301***|0.0314***|-0.00967*|0.0455***|
||(0.00226)|(0.00215)|(0.00509)|(0.00512)|(0.00495)|(0.00997)|
|_Firstborn girl_ * _Post1_|-0.0197***<br>(0.00157)|-0.0213***<br>(0.00165)|-0.0217***<br>(0.00154)|-0.0231***<br>(0.00180)|-0.0224***<br>(0.00183)|-0.0213***<br>(0.00310)|
|_Firstborn girl_ * _Post2_|-0.0372***<br>(0.00249)|-0.0400***<br>(0.00248)|-0.0400***<br>(0.00199)|-0.0418***<br>(0.00225)|-0.0401***<br>(0.00222)|-0.0427***<br>(0.00361)|
|_Ideal fraction of sons_||||0.0126***<br>(0.00349)|-0.0143***<br>(0.00332)||
|_Ideal no. of children_||||0.0273***<br>(0.00152)|0.0275***<br>(0.00162)||
|_Firstborn girl_ * _Ideal fraction of sons_|||||0.0766***<br>(0.00480)||
|_Firstborn girl_ * _Ideal no. of children_|||||-0.000471<br>(0.000968)||
|N|2,455,633|2,455,633|2,455,633|2,276,264|2,276,264|2,276,264|
|_Xi_|x|x|x|x|x||
|Year FE|x|x|x|x|x|x|
|State FE|x|x|x|x|x||
|Age FE|x|x|x|x|x|x|
|Parity FE|x|x|x|x|x|x|
|State x Year FE|x|x|x|x|x|x|
|Years since last birth FE||x|x|x|x|x|
|Firstborn girl x State FE|||x|x|x||
|Mother FE|||x|x|x|x|

NOTES: Coefficients from specification (2) estimated using OLS regression on the mother-year sample. The dependent variable is an indicator for birth to a given mother in a given year. Sample includes all mothers who have ever given birth, for each year from their year of marriage to the year of interview. Standard errors in parentheses are clustered by state. Data: NFHS. *** 1%, ** 5%, * 10%.

43
median branch.<sup>27</sup> Thus, the growth in deposits was accompanied by increased savings across economic strata.<sup>28</sup>

# **_A. Stanbic Branch Summary Statistics, Stratified by Income, Population Density, and Competition_**

Table 7 offers summary statistics that group branches by characteristics of the districts in which they reside. The first two rows indicate that the median Kampala branch is more profitable, has a higher share of loans to deposits, and a lower share of total expenses to assets than the median branch located outside that district. We focus on median values because outliers have substantial influence on the mean values for these indicators. Mean values do however appear in parentheses below the medians. Kampala branches also have more rapid growth in assets, deposits, and the number of depositors. However, branches outside Kampala hold a substantial edge in the growth of total advances (i.e., lending). Again, many of these branches started from a low credit base after privatization, which helps account for their high growth figures.

Outside of Kampala, district characteristics do not appear to have a large effect on the indicators in Table 7. For example, branches located in districts with above-median household expenditures (our proxy for income) perform similarly to branches in belowmedian income districts. Comparisons also tend to be similar when branches are stratified by district population density or by competitive pressures (measured as the share of nonStanbic branches in a district). One slight exception is that profitability tends to be higher in high-income, high-density districts, where Stanbic comprises less than half of all branches.<sup>29</sup> A more notable exception to the general similarity of results for branches

> 27 We discuss the median branch in these paragraphs because the mean values are heavily influenced by outliers. For example, newer branches started with very few depositors. Thus, the average branch had a 1700 percent increase in the number of depositors, but that is driven by 206,000 percent growth at one branch that had almost no depositors at the beginning of the period.

> 28 It has been pointed out to us that some of Stanbic’s growth in deposits might be attributable to its privileged position within the payments system and as processor of government payroll transactions. For example, we were told that increased pay for teachers might have automatically ended up in Stanbic accounts. We note, however, that Stanbic’s growth in real deposits was not substantially different from the sector as a whole, and in fact was a bit slower: Stanbic, 8.0 percent in 2003, 3.3 percent in 2004; sector as a whole (excluding Stanbic), 16.7 percent in 2003, 8.7 percent in 2004. It therefore seems unlikely that any deposit ‘windfalls’ are having large effects on Stanbic.

> 29 This could be because the high-income clients residing in those districts are better able to afford a wider array of financial services.

24
- 32 -

# (a) Targetting Input-Intensive Technology

63. Attempts to introduce Input intensive technology has not met with much success in SSA. These attempts failed because of a failure to take into account local resource endowments and farming systems. Farmers will only adopt new technologies and use new inputs if they reduce the unit cost of production [including the implicit cost of family labor and the opportunity cost of land]. The intensive use of inputs will reduce the unit cost of production in some conditions, but not in others.

64. In land abundant areas such input technologies are not generally attractive to farmers. The strategy implied in using these inputs is to increase yields per unit area, and hence reduce the area needed to produce a given level of output. When land is plentiful this strategy does not provide the farmer with any appreciable saving, since the opportunity cost of land is negligible.5/ By reducing the area needed to provide a given output, input intensive technologies also reduce the labor needed in land preparation, planting and weeding. But this saving in labor costs is usually less than the cash and labor costs required for incorporating these yield innovations into the system. Consider the profitability of using

- 5/ A look at Uganda research and extension efforts over fifty years, from 1910 illustrates this problem. A major research program in Uganda was directed at developing and promoting high-yielding varieties, in conjunction with the fertilizers, better crop husbandary, and improved land management. Farmers simply did not adopt most of the proposed Innovations, on the other hand, they readily adopted new crops such as cotton by expanding their cultivated areas. Increase in population density will make land scarce and valuable so that research of the type pursued almost a century too early will become appropriate. Indeed, some of the earlier findings will still be valid.
off the productivity growth, human capital growth, or both to zero. The simulated paths of the real GDP per capita of these simulations, are labeled as ”No g h,” ”No g ~~A~~ ,” and ”Neither,” respectively, in Figure 12. This shows that Korea’s growth would have been much lower if the promotion of investment and labor market demographic factors had been the only sources of growth.

In the year of 2014, Korea’s real GDP per capita is $34,300 in 2011 USD using national prices and $35,103 using PPP adjusted prices and population data in PWT 9.0. The Korea’s PPP-adjusted real GDP per capita in 2014 is slightly lower than that of Japan ($35,358) and a little higher than that of Spain ($33,864) in the same year. In 1960, Korea’s PPP-adjusted real GDP per capita was $1,175 which was lower than those of Kenya, Tanzania, Bangladesh and Haiti, while those of Japan and Spain were $5,351 and $5,741. Without human capital growth, Korea’s 2014 real income level would have been $14,597 (close to level of Brazil in 2014). Without productivity growth, Korea’s 2014 real income level would have been $12,178 (close to level of South Africa in 2014). With neither of productivity and human capital growth, Korea’s 2014 real income level would have been $5,970 (close to level of Bolivia in 2014). The above comparison clearly illustrates that main backbones of Korea’s ”miraculous growth,” as is asserted by Lucas (1993), are the productivity growth and human capital accumulation, although demographic changes in labor market and investment promotion also played an important role. That is, Korea’s growth experience shows that for successful and sustainable growth, the most critical factors are productivity and human capital growth, i.e., the fundamental sources of long-run growth rather than the sources of transitional growth, as most of the growth models assert.

# **5 Conclusion**

Korea’s remarkable growth experience itself may inspire the developing world because Korea started such development from a comprehensive set of adverse conditions (colonization, massive civil war, corruption, a lack of physical and human resources, political instability and incessant ideological conflicts etc.) that are often mentioned as critical barriers to development among current developing countries. However, without knowing what is actually behind such a growth 30
# TABLE OF CONTENTS

|I.|Inter|national Trade and Transport Problems in the Maghreb ........<br>.....|1|
|---|---|---|---|
||A.|Measuring Transport costs|1|
||B.|Equivalence Between Excess Transport costs and Tariffs.|2|
||C.|The C.I.F./F.O.B. Approach and its Limitations.|2|
||D.|The Current Approach and its Limitations.|4|
||E.|Estimating Excess Costs.|6|
||F.|Estimating Benefits from Removing Transport Barriers ....<br>.......|8|
|II.|Ident|ification and Quantification of Restrictive Practices: Case Studies ...<br>...|10|
||A.|Voyage Cost Analysis: Export of Glucose from Morocco to Tunisia .. .|10|
||B.|Excess Cost Calculations: Transport Chain Case .11||
|||Morocco: Transport Chain for Clothing and Footwear .12||
|||Tunisia: Transport Chain for Citrus Fruits .13||
|||Algeria:<br>Transport Chain for Power Network Equipment ....|16|
|ANN|EXES|||
|Al|Calc|ulation of Ad Valorem Excess Costs: .......................|18|
|A1.1||Algeria .<br>.......<br>......<br>...<br>.....................|19|
|A1.2||<br>Morocco ..............|20|
|A1.3||Tunisia ..............|21|
|A2|Regi|onal Profile of Trade in the Maghreb .......................|22|
|A3|Logi|stical Constraints Affecting Trade in the Maghreb Countries - Diagnosis . .|24|
|||Barrier Ratings ................................|24|
|||<br>Import-Related Barriers ..............................|32|
|||<br>Export-Related Barriers ..............................|36|
|||<br>Infrastructure and Equipment-Related Barriers .....<br>...........|37|
|||Trans-Maghreb Barriers .............................|39|
|A4|Mat|rix of Recommendations for Corrective Measures ................|43|
A-3: **Public Sector Wages,** _Manufacturing Wages and Per Capita GDP, all countries, recent years_

|I:|Africa ...........................|41|
|---|---|---|
|II:|Asia ...........................|41|
|III:|Eastern Europe and Former USSR ...........................|42|
|IV:|Latin America and Caribbean ...........................|42|
|V:|Middle East and North Africa ...........................|43|
|VI:|OECD Countries ...........................|43|
|**Methodological**|**and Technical Notes ......................................**|45|
|Sources**...............**|**......................**|49|
children are typically in the same village small group (a sub-village administrative unit) and live in close proximity with one another. Given increases in housing wealth accumulated in rural areas since the mid-1980s, the trend toward nuclear families may well signal a wealth effect independent of the traditional value of providing support and care to elder parents.

A more important concern may be the proximity of adult children, and not whether they co-reside. In Figure 2 we summarize the living arrangements by age cohort from a supplemental survey conducted in 2004 with the Research Center for the Rural Economy (RCRE) at China’s Ministry of Agriculture (and which is discussed below), and includes information on children living within the same village as their elders. While co-residence with adult children was common for fewer than 60 percent of respondents among those aged 60 to 70, more than half the elderly living alone or with a spouse in this age range had at least one adult child living in the village.<sup>6</sup> This suggests that while co-residence was well below levels of the 1930s, adult children were still potentially available to provide both instrumental care and financial support. As elder parent age increases, the probability of co-residence with an adult child approaches 100 percent.<sup>7</sup> Decline in co-residence reflects a decline in support for the elderly only if it is associated with increased elderly abandonment. The rural elderly may have sufficient support if they are receiving transfers from local or migrant adult children. Moreover, the adult children of rural elderly who have become infirm may yet respond to traditional values and return to care for their parents. Giles and Mu (2007) explore this possibility conducting separate analyses using two different data sources (the CHNS and the RCRE surveys), and find a significantly lower

> 6Note that co-residence in rural areas of the four RCRE provinces was also somewhat higher than what we observe for rural areas of the CHNS panel.

> 7Of course, two very different conclusions are consistent with evidence of greater incidence of co-residence with age in a simple cross-section: the oldest, who are more likely to be infirm, tend to move in with adult children; alternatively, if co-residence does have an impact on the quality of care provided, then perhaps only the elderly living with adult children reach old age.

9
1

# 1. Introduction

There is an extensive literature on hospital cost functions for industrialized countries, but a much smaller literature for developing co: 'tries.1 Yet the issues facing policy-makers in both sets of cot .tries are much the same: Are hospitals over-capitalized, as is often claimed of US hospitals? Are hospitals inefficient in other respects? Do hospitals vary in their degree of inefficiency? Are private hospitals more efficient than their public counterparts? Should hospitals specialize or provide a broad range of services? Could costs be reduced by concentrating cases in fewer hospitals? Such issues are as relevant to policy-makers in developing countries as to their counterparts in the industrialized world.

Moreover, it seems likely that the econometric techniques that have been used to such effect in the industrialized world would be equally capable of informing policy debate in the developing world. Our purpose in this paper is to provide a survey of these techniques and to summarize the work to date on developing countries. Though the paper is written primarily with developing countries in mind, it is hoped that it may be of some value to researchers in industrialized countries. Our survey of econometric techniques is not uncritical. We question, for example, the validity of recent tests of over-capitalization undertaken on American hospitals. We also make various general observations about the methods used to investigate economies of scope and economies of scale.

Section 2 provides a survey of the issues facing policy-makers in the hospital sector and the relevant econometric techniques. sections 3 to 6 contain surveys of four recent studies of hospital costs in Kenya, Peru, Ethiopia and Nigeria. The final section contains our conclusions concerning both the studies undertaken to date and the methods for analyzing hospital costs.

# 2. **Some** economics and econometrics of hospitals

As indicated above, there are, broadly-speaking, four sets of policy issues that can be addressed using cost function analysis: (i) are hospitals over-capitalized?, (ii) are hospitals inefficient?, (iii) should hospitals specialize or provide a broad range of services?, and (iv) are there too many hospitals?

# 2.1 Are hosoitals over-canLtalized?

The issue is whether hospitals have a capital stock that is too - large given their output level. In developed countries especially the United States - it is often argued that this is the case, the '. For reviews of the American and British literature see Cowing, Noltmann and Peters (1983) and Wagstaff (1989a). Several of the more recent studies for industriaLized countries are referred to in the present paper. To our knowledge there has been no survey of developing country studies.
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- 2012, _335_ (6067), 405–406.

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- **Traub, Lulama Ndibongo and Thomas S Jayne** , “The effects of price deregulation on maize marketing margins in South Africa,” _Food Policy_ , 2008, _33_ (3), 224–236.

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23
basis, to effectively compete in services ―trade,‖ it still is likely that it requires more of a domestic presence than trade in goods.<sup>4</sup> Given the key role of FDI in the effective delivery of services, commitments to foreign investors are key aspects of trade negotiations in services. With the growing importance of services trade and FDI in services, it is important to have a framework with which we can analyze the impacts of liberalization of barriers to FDI in services.

The way my co-authors and I have modeled services builds crucially on the growing body of empirical evidence that shows that increased access to services, increased foreign direct investment in services or services liberalization increases the productivity of the manufacturing sectors and of the economy as a whole. (See Rutherford and Tarr, 2008, 2010; Markusen, Rutherford and Tarr, 2005; Jensen, Rutherford and Tarr, 2006, 2007, 2010; Balistreri, Rutherford and Tarr, 2009; Jensen and Tarr, 2008, 2011; Balistreri and Tarr, 2011.) Further there is evidence that increased access to imported intermediate goods increases economy-wide productivity. I summarize the computable general equilibrium modeling literature on services below, where I argue that our approach is the first to incorporate the liberalization of barriers against foreign direct investment in services where endogenous productivity impacts play an important role in the results. In our full applied models, we also incorporate the endogenous productivity impacts from increased access to intermediate goods. My co-authors and I have shown that in applications where liberalization of barriers against foreign investors in services is important, such as in accession to the World Trade Organization, the estimated welfare gains depend crucially on our modeling framework—our approach yields estimated welfare gains that are several multiples of the estimated gains of models without foreign direct investment in

> 4 Data on the sales of foreign affiliates of U.S. firms suggests that sales through FDI is the most important channel for U.S. firms to sell services to foreigners (Francois and Hoekman, 2010, p.655).

3