rafmacalaba/datause-encoder-data huggingface dataset:
Allen et al. (2005) are based largely on anecdotal evidence and on the analysis of the 17 largest, and perhaps unrepresentative, firms in the two most developed regions in the country. Finally, their definition of informal financing channels includes retained earnings, informal financing, equity issuance and all other sources of funds except bank loans, state funding and foreign investment.

Ayyagari, Demirguc-Kunt, and Maksimovic (2010a) use data on 2400 firms (including 1720 non-publicly traded and non-state companies) from China and confirm the wide use of financing channels other than bank finance. They find that only 20% of firm financing in their sample is sourced from banks, which is comparable to the use of bank financing in other developing countries, such as India, Indonesia, Brazil, Bangladesh, Nigeria, and Russia (see Table 8 below). However, they also find China has the smallest ratio of Internal Financing/Retained Earnings (only 15.24%) compared to all the other emerging markets. Further, while the use of funds from Family and Friends and Informal lending sources such as money lender or informal banks seems to be comparable with its use in other countries, China also has the highest average amount of Other Financing (42.70%) compared to the other developing countries.

When they look at the association between financing patterns and growth, they find that it is the formal financing channel, specifically bank finance that is positively associated with higher growth and reinvestment. They find no evidence that alternative financing channels such as informal sources have a positive impact on growth and reinvestment or that they substitute for the formal sector.

Their results are consistent with other studies emphasizing the role of institutions and formal finance in China. Cull and Xu (2005) find that profit reinvestment rates are affected by enterprise managers' perceptions about the security of property rights, the risk of expropriation by government officials, the efficiency and reliability of courts, and access to credit. In a more recent paper, Cull, Xu, and Zhu (2009) find that despite a biased and inefficient banking system, trade credit does not play an economically significant role in China. Cheng and Degryse (2006) explore the impact of the development of bank versus non-bank financial institutions on the growth rate of Chinese provinces over the period 1995-2003 and conclude that only bank loans 59
# **References**

Ando, Mitsuyo and Fukunari Kimura, (2003) “The Formation of International Production and Distribution Networks in East Asia” _NBER Working Papers_ No. 10167 Ando, Mitsuyo and and Fukunari Kimura, (2007) ““Fragmentation in East Asia: Further Evidence”, mimeo.

Athukorala, Prema-Chandra and Nobuaki Yamashita (2005) “Production Fragmentation and Trade Integration: East Asia in a Global Context.” _North American Journal of Economics and Finance_ , forthcoming.

Finger, J. M. and M. E. Kreinin, (1979). “A Measure of `Export Similarity' and Its Possible Uses.” _The Economic Journal_ , Vol. 89, No. 356. pp. 905-912 Jones, Ronald W. and Henryk Kierzkowski (2001) “A Framework for Fragmentation.” in Fragmentation: New Production Patterns in World Economy. Sven W. Arndt and Henryk Kierzkowski eds., Oxford University Press.

Kawai, Masahiro (2005) “Trade and Investment Integration and Cooperation in East Asia: Empirical Evidence and Issues” in _Asian Economic Cooperation and Integration: Progress, Prospects, and Challenges_ , Asian Development Bank.

Kimura, Fukunari, Yuya Takahashi, and Kazunobu Hanazawa (2005), “Fragmentation and Parts and Components Trade: Comparison between East Asia and Europe.” Mimeo. Kokko, Ari, (2002) “Export-Led Growth In East Asia: Lessons For Europe’s Transition Economies. Stockholm School of Economics, Working Paper no. 142.

Lall, S. (2000), “The Technological Structure and Performances of Developing Country Manufactured Exports, 1985-98”, Oxford Development Studies, vol. 28, no.3, pp. 337369 Gaullier, Guillaume, Françoise Lemoine, Deniz Ünal-Kesenci. 2005. “China’s Integration in East Asia: Production Sharing, FDI & High-Tech Trade.” _CEPII Working Paper_ , no.9. Schott, Peter (2004) “Across-Product Versus Within-Product Specialization in International Trade.” _Quarterly Journal of Economics_ , 119 (2): 647-678.

> <sup>17</sup>
Policy Research Working Paper 7110

# **Abstract**

This paper provides the first systematic empirical assessment of the pace at which housing investment has responded to rising demand from urbanization. The assessment used National Accounts Statistics to build a data set of residential housing investment for more than 90 countries. The data set explicitly accounts for investment by households, the government, and the private sector. The analysis finds that housing investment follows an S-shaped trajectory taking off around per capita GDP of about $3,000 (US$2005) and tapering down at per capita GDP around $36,000 (US$2005). The analysis also finds that between 2001 and 2011, housing investment in low-income economies averaged 4.56 percent of gross domestic product and 9.12 percent in upper-middle-income economies. An important finding is that countries in Sub-Saharan Africa have housing elasticities similar to comparable low-income and lower-middle-income economies. In financing housing investment, the paper finds that developing countries tend to rely much more on domestic savings and government debt, whereas high-income Organisation for Economic Co-operation and Development countries lever capital markets by tapping foreign savings. Not only does excessive reliance on domestic savings and government debt increase the sensitivity of housing investment to the cyclicality of growth of gross domestic product, it also can potentially crowd out investments in health and education.

This paper is a product of the Social, Urban, Rural and Resilience Global Practice Group. 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://econ.worldbank.org. The authors may be contacted at slall1@worldbank.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
In a utilitarian tradition<sup>1</sup> , this paper approximates utility by exploiting data on subjective life satisfaction in Venezuela. The author and a co-researcher asked a diversified sample of 400 Venezuelans to report their satisfaction with life. In order to test for the significance of perceived relative income of reference groups, a specific questionnaire was constructed to collect data on subjective relative income of siblings, parents, friends, and of the individual itself in the past. Using data from a middle-income country, the sample avoids the dominance of extremes in the data, such as wide-spread poverty at subsistence levels or post-materialist concerns on the other side of the spectrum.

The paper is organized in five sections. Following this introduction, Section 1 outlines the conceptual approach of the analysis and presents previous findings in the life satisfaction literature, which inform the model estimated. Section 2 gives an overview of the use of reference points in previous research and in this paper. The data used for the empirical analysis is described in Section 3. Section 4 discusses the model, presents the estimations, and provides an interpretation of the results. Section 5 concludes.

# **1. Conceptual Approach**

# 1.1 _Self-Reported Life Satisfaction as a Measure of Income Utility_

In economics the dominant tendency has been to refer to preferences ‘revealed’ in market exchanges to measure utility derived from income. As a consequence, higher absolute income translates into higher consumption, which is equated with higher utility. This conventional view has severe shortcomings, for instance, if individuals derive utility from relative standing or status. Market purchase data also fail to adequately

> 1 Traditionally, utilitarians like Bentham (1789) related the term ‘utility’ with happiness. In this paper, the terms ‘utility’, ‘happiness’, ‘life satisfaction’ and ‘well-being‘ are consequently used interchangeably in the discussion of the literature. ‘Life satisfaction’ was deliberately chosen as wording in the questionnaire instead of ‘happiness’, as it is seen to better reflect the constant, overall notion of happiness which is of interest when approximating utility.

3
Kellenberg, Derek K., 2009, “US Affiliates, Infrastructure and Growth: A Simultaneous Investigation of Critical Mass,” _Journal of International Trade and Economic Development_ , 18 (September), 311-45.

Kneller, Richard, Michael F. Bleaney, and Norman Gemmell, 1998, “Growth, Public Policy and the Government Budget Constraint: Evidence from OECD Countries,” Discussion Paper No. 98/14, School of Economics, University of Nottingham.

Kneller, Richard, Michael Bleaney, and Norman Gemmell, 1999, “Fiscal Policy and Growth: Evidence from OECD Countries,” _Journal of Public Economics_ , vol. 74, no. 2, 171-190.

Lee, Young and Roger H. Gordon, 2005, “Tax Structure and Economic Growth,” _Journal of Public Economics_ , 89:1027-1043.

Levine, Ross and David Renelt, 1992, “A Sensitivity Analysis of Cross-Country Growth Regressions,” _American Economic Review_ , vol. 82, no. 4, 942-63.

Looney, Robert and P.C. Frederiksen, 1986, “Profiles of Current Latin American Military Producers”, _International Organization_ , 40(3): 745-752.

Moreno-Dodson, Blanca, 2008, “Assessing the Impact of Public Spending on Growth: An Empirical Analysis for seven fast Growing Countries,” World Bank Policy Research Working Paper No. 4663.

Park, Hyun, 2006, “Expenditure Composition and Distortionary Tax for Equitable Economic Growth,” IMF Working Paper No: WP/06/165.

Pushak, Tearas, Erwin R. Tiongson, and Aristomene Varoudakis, 2007, “Public Finnace, Governance, and Growth in Transition Economies,” World Bank Policy Research Working Paper No. 4255.

Rogers, Mark L., 2008, “Directly Unproductive Schooling: How Country Characteristics Affect the Impact of Schooling on Growth,” _European Economic Review_ , 53, 356-85.

Schaltegger, Christoph A. and Benno Torgler, 2006, “Growth effects of public expenditure on the state and local level: evidence from a sample of rich governments,” _Applied Economics_ , 2006, 38, 1181–1192.

Segura-Ubiergo, Alex, Alejandro Simone, Sanjeev Gupta, and Qiang Cui, 2009, “New Evidence on Fiscal Adjustment and Growth in Transition Economies,” _Comparative Economic Studies_ , 2009, 1–20.

Slemrod, J., 1995, “What Do Cross-Country Studies Teach about Government Involvement, Prosperity, and Economic Growth?” _Brookings Papers on economic Activity_ , pp.373-431.

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increase in driving for drastic restrictions and the slight CO increase in the morning peak. This finding is also in line with Eskeland and Feyzioglu (1997a), who found that HNC increased car use.

The long-run price elasticities oscillate between -0.12 and -0.18, though they are statistically insignificant. The long-run income elasticities vary from 0.63 to 0.73 and are statistically different from zero at conventional significance levels. These values are in the range of the elasticities reported by Dahl (2012)—between -0.04 and -0.69 for price and between 0.23 and 2.06 for income—using studies from 124 countries varying in scope and methodology.

In contrast, the estimates of the ECM analysis show that neither the moderate nor the drastic phase of PYP led to short-run reductions in gasoline consumption for any of the specifications (panel (b) in table 5). This result is supported by the lack of evidence of reduced CO across all time-interval subsamples in both phases of the program and by the magnitude of the monthly rate of adjustment of gasoline consumption toward the long-run equilibrium—for example, between 27 percent and 31 percent of the adjustments happen in the first month. As regards the elasticities, the price elasticity estimates show a higher response of the gasoline demand to pricing in the short run than in the long run. Eskeland and Feyzioglu (1997b), who studied the gasoline demand in Mexico, found results in the same direction.

Considering that gasoline consumption is responsive to prices in the short run and that the monthly gasoline demand in Bogotá decreased from 42 to 24 million gallons from 1996 to 2008, it seems reasonable that gasoline prices were responsible for some fraction of that decline right after a price increase. Thus, in some way, prices rather than PYP have tended to discourage driving. However, the fact that the 18
# **3. Potential technology options of biofuels**

The Chinese government highly emphasized the non-grain (non-food oil) development path in various policy documents, i.e., the Medium and Long Term Renewable Energy Development Plan by NDRC, the Agricultural Bioenergy Development Plan (2007-2015) by the Ministry of Agriculture, and the Issues on Development and Promotion of Oil Plants by General Office of State Council. In this study, we discuss different technology options allowed under these plans. These options include: (i) fuel ethanol from non-grain starch and sugar crops, (ii) biodiesel from oil bearing trees, (iii) biodiesel from waste oils, and (iv) biofuels from cellulosic biomass (second-generation biofuels). For each technology, we first present resource potential followed by supply costs and key challenges.

# **3.1 Fuel ethanol from non-grain starch and sugar crops**

Starch and sugar crops are currently the dominant feedstocks for the production of biofuels, and ethanol is by far the most important fuel derived from these crops. Corn-based ethanol accounts for more than 89% of fuel ethanol production in the United States (calculated based on RFA, 2011). The same is true for China, where the major feedstocks are by far corn and wheat with market share of more than 80%. However, as discussed above, no new projects based on these feedstocks are allowed; therefore, this paper focuses on alternative non-grain sugar and starch energy crops, involving cassava, sweet sorghum and sweet potato.

# **3.1.1 Resource potential**

The available land resource for feedstock production is one of the major determinants of the development of biofuels. China has limited land resources but huge population. To meet the growing food demand and grain self-sufficiency rate target<sup>2</sup> , the land management policies are very strict. Therefore, it is necessary to find available land for biofuels development, which compliances with current land management and food security policies. In line with the Land Administration Law, RGCREDS (2008) classifies marginal land into two parts: (i) unutilized land and (ii) part of low-productive arable land. Based on some preliminary researches on land suitability assessment, the marginal land available for three types of feedstocks is shown in Table 3. The total marginal land available for these feedstocks is 23.73 million hectare and corresponding potential for ethanol production could be 65.48~88.57 million tonnes. Although there might be high uncertainties on the yields, the available marginal land indicates that land supply would not be a barrier to meet China’s biofuels targets in 2020. Note however that marginal lands do need water resources, fertilizers and so on. If these resources are provided, one might argue that the land can be used for production of food instead of biofuels, if food security is the primary concern of the country.

> 2 Grain self-sufficient rate is defined as the ratio of domestic consumption and domestic productions of grains. According to the _National Framework for Medium- and Long-term Food Security_ , grain self - sufficiency rate is required above 95% by 2020.

6
move to sell off a controlling stake in National Microfinance Bank (NMB) to a foreign strategic investor with strong experience in rural credit appears to have paid off through an introduction of innovative new products and approaches to agricultural finance and microfinance. Besides crop finance, banks and microfinance institutions have made limited headway in finding secure and cost-effective ways of lending for agricultural finance.

The banking sector, however, performs only a very limited role in the economy, even by Sub-Saharan African standards. Private sector credit remains limited, short-term interest rate spreads are high, banks continue to invest approximately half their deposits in government securities (although loan to deposit ratios have improved in recent years), and banks maintain significant offshore foreign currency deposits (about 39% of total deposits as of October 2007). Housing finance is negligible as residential mortgages represent less than 1% of all bank loans.

In order to develop new business models and lending technologies, the key task for government will be to ensure the legal and information infrastructures for banks and other financial institutions are in place. The general credit culture and institutional framework for contract enforcement remains underdeveloped and this has inhibited the growth of financial markets. The almost total absence of a mortgage market is a reflection of both the uncertainty concerning land title and the inability to enforce a contract.

Foreign banks, particularly the new entrants, have been challenged in mobilizing local currency for lending to match both their capital and institutional capacity. A better-developed interbank market would serve to extend the provision of credit within the domestic financial system. In 2008, shilling deposits were held largely by the three large domestic banks.

The efficient operation of the financial markets can be much assisted through the effective use of registries such as a land registry, company registry and a movable collateral registry. In addition, banks in particular are supported in their lending activities through the use of credit information bureaus. While these registries exist in Tanzania, their usefulness has been impeded by relatively weak implementation (and, in the case of the credit bureau, limited cooperation from the larger banks).

Although the Bank of Tanzania has substantial operating independence on banking supervision matters, some features of the legislation have the potential to compromise its 22
# **3.2.4 Summary**

Without understating the methodological limitations of each approach, the main messages emerging from firm-level studies, industry-level studies, country case studies and randomized experiments point to a similar conclusion: Direct access to finance critically and positively affects firm performance. This is in contrast to findings for households, where the impact of direct access is much less clear. More importantly for the purposes of this paper, the empirical research also highlights a distributional effect. Financial development exerts a particularly positive impact on small firms, and facilitates the entry of new firms. These results are important because the bulk of the labor force is employed by small and medium enterprises in developing countries, so any disproportionately positive impact on them would have significant labor market effects for the poor.

# **_3.3 Impact at the Aggregate Level_**

In examining the relationship between finance, income inequality, and poverty at the aggregate level, it is helpful to recall that (1) a large literature finds that financial development – as measured by measures of depth, such as credit extended to the private sector divided by GDP per capita - accelerates aggregate economic growth and (2) there is an identity linking aggregate growth, income of the poor, and inequality. Specifically, if Y _P_ equals the per capita income of the lowest quintile, Y equals average income per capita, and L is the Lorenz curve which relates the share of income received to the share of the population, then Yp = Y*L(0.2)/0.2. Differentiating with respect to time and letting g(x) represent the growth rate of variable x yields g(Y _p_ ) = g(Y) + g(L(0.2)). The growth of per capita income of the poorest quintile equals the growth of average per capita income plus the growth of the Lorenz curve, which captures changes in income distribution. Thus, if financial development does not intensify income inequality (too much), financial development will reduce poverty by boosting overall economic growth. If, however, financial development intensifies income inequality, then this income distribution effect could negate – or even reverse – the poverty-reducing influence of financial development that operates through overall growth. Or, finance might disproportionately help the poor, in which case financial development would affect poverty through two channels: overall growth and a flattening of the distribution of income.

36
|**Table 1: Enterprise S**<br>**the DBvalue**|**urvey avera**<br>Impor|**ge value re**<br>ts|**ported by fir**<br>Constructio|**ms by coun**<br>n Permit|**try regress**<br>Operating|**ed on**<br>License|
|---|---|---|---|---|---|---|
|||OLS regr<br>|ession<br>||||
|**Constant**|5.99||52.49||36.22||
|**Slope**|0.14||0.05||0.00||
|**N**|91||74.00||87.00||
|**R-Squared**|0.129||0.03||0.00||
|**t-test, β=0**|0.000||0.07||0.49||
|**t-test, β=1**|0.000||0.00||0.00||
|||**Quar**|**tic**||||
|**Slope at 10**<sup>**th**</sup><br>**percentile (value)**|0.482|10|0.29|137|1.12|7|
|**Slope at 50**<sup>**th**</sup><br>**percentile (value)**<br>|0.073|23|0.08|210|-0.05|31|
|**Slope at 90**<sup>**th**</sup><br>**percentile (value)**|0.224|43|-0.09|381|0.16|95|
|**R-Squared**|0.160||0.08||0.01||
|||**Spine at**|**median**||||
|**Slope below (value**<br>**at kink)**|0.25|23.00|0.21|210.00|0.32|31.00|
|**Slope high**|0.11||0.01||-0.06||
|**p-value**|0.38||0.17||0.60||
|<br>|**Two**<br>|**splines, at**<br>|**thirds of DB**<br>|<br>|||
|**Slope below**<br>**(value at 1**<sup>**st**</sup>**kink)**|0.31|18.00|0.47|174.00|0.99||
|**Slope between 1**<sup>**st**</sup><br>**and 2**<sup>**nd**</sup>**kink (value**<br>**at 2**<sup>**nd**</sup>**kink)**|0.13|32.00|-0.09|255.00|-0.27||
|**Slope above second**<br>**kink**|0.11||0.04||-0.04||
|**p-value**|0.63||0.18||0.71||
||<br>**Two spline**|<br>**s (goodnes**|<br>**s of fit maxi**|**mizing)**|||
|**Slope low**|-0.07|10.00|0.27|234.60|0.63|42.20|
|**Slope medium**|1.08|13.30|-0.27|332.20|-2.97|51.00|
|**Slope high**|0.11||0.13||0.12||
|**p-value**|0.38||0.06||0.35||
|Source: Author‘s calcu|lations based|on ES and|DB data.||||

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