rafmacalaba/datause-encoder-data huggingface dataset:
1.2 cross-country evidence on revenue recovery

7

- Inflation: reflects the extent to which revenue is generated from seigniorage, which needs to be controlled for.

- VAT: a modern VAT regime that is strictly enforced is associated with increased domestic revenue collection; however, a weakly enforced VAT system with widespread exemptions could be revenue-reducing compared to taxes collected at fixed border points.

# 1.2.2 _Data_

The IMF’s Government Finance Statistics is the best publicly accessible source for cross-country data on tax revenue, but it is incomplete and suffers from mismeasurement. I therefore use the same panel data as that used by Baunsgaard & Keen (2010) who adjust the GFS data by cross-checking numbers with internal IMF figures obtained through (“Article IV”) consultations with individual countries. They try to correct a common flaw in many countries where tariff and VAT revenues are conflated if they are both collected at the border. This would be problematic for the exercise in this paper because the aim is to find out whether decline in tariff revenues are made up for by domestic sources like VAT and excise.

I make three modifications to Baunsgaard and Keen’s data set. First, their data on VAT is only a binary variable of whether the country had VAT in place in the year concerned. I use in its place actual ad valorem rates, compiled from three different sources as follows: Krever (2008), Ernst & Young (2008) and World Bank 2011 _a_ . Second, I confine my analysis to 40 low-income countries over a shorter time period of 25 years, from 1982 to 2006.<sup>11</sup> Third, I use two new measures for a country’s abundance in natural resources as an additional explanatory variable. The first measure is the per capita natural resource-based exports (belonging to

> 11 Five countries drop out of the regression because of incomplete data on inflation and per capita income, as follows: Comoros, Guinea, Myanmar, Sao Tome and Principe, and the Solomon Islands.
private goods remains roughly constant over time (independent of whether booms or busts are occurring). With these additional assumptions, welfare is maximized by a strategy that not only smooths private and public consumption intertemporally, but also keeps their respective shares of GN)P roughly constant during temporary export booms or busts.41 If one sees a sharp increase or decrease in the public consumption share, after accounting for any countercyclical stabilization policy that may be warranted (which, by the way, would tend to reduce -- not increase -- government spending), there is a strong a priori presumption that the increase in public consumption is excessive.

The pattern of public and private in Colombia before, during, and after the 1976-80 coffee boom provides a striking example. The share of central government consumption rose sharply from 8 percent in 1977, the peak of the boom, to almost 12 percent by 1983. (Because these figures refer only to the central government, they do not include increases in public consumption). Even as the boom subsided, the ratio of government consumption). Even as the boom subsided, the ratio of government consumption to GDP continued to rise. This phenomenon is not unique to Colombia. Rajaram's 1985 study of Sub-Saharan africa finds a similar pattern: government expenditures surge during booms, and are very difficult to cut back after the export boom ends.

4/ This point has been emphasized in Cuddington (1986) where it is argued that the difficult political economy question of the "appropriate" size for the public sector should be kept distinct from the question of how to manage temporarry export booms. During booms, the argument in the text suggests that the relative shares of the private and public sector in total consumption should be held roughly constant. A massive expansion in the public sector, which often occurs during booms, should be considered undersirable. It is self-delusion to justify it on the grounds that the size of the public sector was in fact too small prior to the onset of the boom.

40
- Sen, A. 1979. “Equality of What?” _The Tanner Lectures on Human Values_ . Stanford University. May 22. Available at: https://bit.ly/2wAYuxI

- Sen, A. 1999. _Development as freedom_ . Oxford: Oxford University Press.

- Simon, H. A. 1957. _Models of Man: Social and Rational. Mathematical Essays on Rational Behavior in a Social Setting_ . New York, NY: Wiley & Sons.

- Snyder, C. R. 2000. “Hypothesis: There is Hope.” In C.R. Snyder (Eds.). _Handbook of Hope Theory, Measures and Applications_ (pp.3-21). San Diego, CA: Academic Press.

- Snyder, C. R., L. Irving, and J. R. Anderson. 1991. “Hope and Health: Measuring the will and the ways.” in C. R. Snyder and D.R. Forsyth (Eds.). _Handbook of social and clinical psychology: The health perspective_ . pp.285-305. Elmsford, New York: Pergamon Press.

- Stark, O. 2006. “Status Aspirations, Wealth Inequality, and Economic Growth.” _Review of Development Economics_ 10 (1): 171–176.

- Steele, C. M. 1997. “A threat in the air: How stereotypes shape intellectual identity and performance.” _American Psychologist_ 52(6): 613–629.

- Stutzer, A. 2004. “The role of income aspirations in individual happiness.” _Journal of Economic Behavior & Organization_ 54 (1):89–109.

- Tajfel, H., and J. C. Turner. 1979. “An integrative theory of intergroup conflict.” in W. G. Austin and S. Worchel (Eds.) _The social psychology of intergroup relations_ . pp. 33–37. Monterey, CA: Brooks/Cole.

- Urzúa, S. 2012. “La rentabilidad de la educación superior en Chile. Revisión de las bases de 30 años de políticas públicas” (The Economic Returns to Higher Education in Chile: Revising the Foundations of 30 Years of Public Policies). _Estudios Públicos_ 125: 2–52.

- Weissberg, R. P., J. A. Durlak, C. E. Domitrovich, and T. P. Gullotta. 2015. “Social and emotional learning: Past, present, and future.” in J. A. Durlak, C. E. Domitrovich, R. P. Weissberg, and T. P. Gullotta (Eds.). _Handbook for social and emotional learning: Research and practice_ . New York, NY, US: Guilford.

- World Bank. 2015. _World Development Report 2015: Mind, Society, and Behavior_ . Washington, DC: World Bank.

- Wydick, B., P. Glewwe, and L. Rutledge. 2013. "Does International Child Sponsorship Work? A SixCountry Study of Impacts on Adult Life Outcomes." _Journal of Political Economy_ 121(2): 393– 436.

- ———. 2017. “Does Child Sponsorship Pay off in Adulthood? An International Study of Impacts on Income and Wealth.” _World Bank Economic Review_ 31(2): 434–458.

33
FIGURE 9 SEIGNIORAGR **E** VENUE <!-- Start of picture text --> 45<br>2.5 - I I<br>2T RA<br>05 2.5 4.5 6.5 85 t5 ... 5 k5 ,5. .ES<br>RIFIATION RAE7<br>COMPUTED FROM MI1 COMIDUTED FROM M2<br><!-- End of picture text --> 3 4
- Blattman, C., Green, E. P., Jamison, J., Lehmann, M. C., & Annan, J. (2016). The returns to microenterprise support among the ultrapoor: A field experiment in postwar uganda. _American economic journal: Applied economics_ , 8(2), 35–64.

- Bossuroy, T., Goldstein, M., Karlan, D., Kazianga, H., Pariente, W., Premand, P., Thomas, C., Udry, C., Vaillant, J., & Wright, K. (2021). Pathways out of extreme poverty: Tackling psychosocial and capital constraints with a multi-faceted social protection program in niger.

- Burke, M., Hsiang, S. M., & Miguel, E. (2015). Climate and conflict. _Annual Review of Economics_ , 7(1), 577–617.

- Carneiro, P. M., Kraftman, L., Mason, G., Moore, L., Rasul, I., & Scott, M. (2020). The impacts of a multifaceted pre-natal intervention on human capital accumulation in early life.

- Carroll, C. (2019). Theoretical foundations of buffer stock saving.

- Carroll, C. D. & Kimball, M. S. (1996). On the concavity of the consumption function. _Econometrica_ , 64(4), 981–992.

- Carter, M. R. & Barrett, C. B. (2006). The economics of poverty traps and persistent poverty: An asset-based approach. _The Journal of Development Studies_ , 42(2), 178–199.

- Croke, K., Hicks, J. H., Hsu, E., Kremer, M., & Miguel, E. (2016). Does mass deworming affect child nutrition? meta-analysis, cost-effectiveness, and statistical power. (22382).

- De Mel, S., McKenzie, D., & Woodruff, C. (2008). Returns to capital in microenterprises: evidence from a field experiment. _The quarterly journal of Economics_ , 123(4), 1329–1372.

- Deaton, A. (1991). Saving and liquidity constraints. _Econometrica_ , 59(5), 1221–1248.

- Fagereng, A., Holm, M. B., & Natvik, G. J. J. (2019). Mpc heterogeneity and household balance sheets.

48
TANZANIA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Table 2. Benchmarking power indicators, 2005-2010**

||Unit|Low-income<br>countries,<br>2006|Tanzania<br>2005/06|Tanzania<br>2008/09|Middle-income<br>countries<br>2006|
|---|---|---|---|---|---|
|Installed power generation<br>capacity|MW/mil. people|24.4|22.3|22.5|796.2|
|Power consumption|kWH/capita|99.5|47.6|80.8|4,473|
|Power outages|Day/year|40.6|63.1|47.3|5.6|
|Firms’ reliance on own generator|% consumption|17.7|12.3|36.8|0.5|
|Firms’ value lost due to power<br>outages|% sales|6.1|—|9.6|0.8|
|Access to electricity|% population|15.4|10.6|14.0|59.9|
|Urban access to electricity|% population|71|38.9|52.0|83.7|
|Rural access to electricity|% population|12.0|1.8|2.0|33.4|
|Growth access to electricity|%<br>population/year|1.4|0.8|—|1.8|
|Revenue collection|% billings|88.2|94.0|94.0|99.9|
|Distribution losses|% production|22.1|26.0|15.4|15.7|
|Cost recovery|% total cost|90.0|41.9|57.1|125.7|
|Total hidden costs as % of<br>revenue|%|121.2|175.3|86.6|3.5|
|US cents|Tanzania<br>2005|Tanzania<br>2010|Predominantly<br>generatio|hydro<br>n<br>O|ther developing<br>regions|
|Power tariff (residential at 75 kWh)|5.5|7.3|10.27||5.0 – 10.0|
|Power tariff (commercial at 900 kWh)|10.1|9.4|11.73|||
|Power tariff (industrial at 50,000 kWh)|9.1|6.2|11.39|||

_Source:_ Eberhard and others 2009. Derived from AICD electricity database, http://www.infrastructureafrica.org/aicd/tools/data and more recent data provided by World Bank staff. For Tanzania, data for 2005 and 2010 are reported to show progress over time. Benchmark data, however, relates to 2006. — = Data not available.

10
- Nelson, A. (2008). _Travel time to major cities: A global map of Accessibility_ , Global Environment Monitoring Unit edn. Joint Research Centre of the European Commission, Ispra Italy.

- Nhu, C. and Noy, I. (2020). Measuring the impact of insurance on urban earthquake recovery using nightlights. _Journal of Economic Geography_ , **20,** 857–877.

- NSO (2012). Third integrated household survey 2010-2011 - final report. Technical Report. Malawi National Statistical Office (NSO) and The World Bank.

- Nunn, N. and Puga, D. (2012). Ruggedness: The blessing of bad geography in africa. _Review of Economics and Statistics_ , **94,** number 1, 20–36.

- Perez-Heydrich, C., Warren, J. L., Burgert, C. R. and Emch, M. (2013). Guidelines on the use of DHS GPS data edn. ICF International.

- Pinkovskiy, M. and Sala-i Martin, X. (2016). Lights, camera ... income! illuminating the national accounts-household surveys debate. _The Quarterly Journal of Economics_ , **131,** number 2, 579–631.

- Pokhriyal, N. and Jacques, D. C. (2017). Combining disparate data sources for improved poverty prediction and mapping. _Proceedings of the National Academy of Sciences_ , **114,** E9783–E9792.

- Pratesi, M. and Salvati, N. (2008). Small area estimation: the eblup estimator based on spatially correlated random area effects. _Statistical Methods and Applications_ , **17,** 113–141.

- Ravallion, M. (2018). Inequality and globalization: A review essay. _Journal of Economic Literature_ , **56,** number 2, 620–642.

- Roberts, M., Blankespoor, B., Deuskar, C. and Stewart, B. (2017). Urbanization and development: is latin america and the caribbean different from the rest of the world? Policy Research Working Paper 8019. The World Bank.

- Searle, S., Casella, G. and McCulloch, C. (1992). _Variance components_ . New York: Wiley.

- Steele, J. E., Sundsøy, P. R., Pezzulo, C., Alegana, V. A., Bird, T. J., Blumenstock, J. and Hadiuzzaman, K. N. (2017). Mapping poverty using mobile phone and satellite data. _Journal of The Royal Society Interface_ , **14** .

57
7 water has deteriorated. Despite the latter, the combined effect is to reduce the proportion of Tanzanians who suffer from any of the three forms of deprivation: this has fallen from 90 per cent to 80 per cent. Equally there has been a fall in the proportion deprived on all 3 dimensions: from 19 per cent to 10 per cent. At the same time, there has been an increase in one category of the deprived: those lacking only access to water.” (Atkinson and Lugo, 2010, p. 15).

**Table 1. Deprivations in schooling, access to protected water and durable assets in Tanzania**

|**Proportion of the individuals living in households ...**|**2001**|**2007**|
|---|---|---|
|**School deprived: at least one child 5-16 years old not in school**|55.2|34.5|
|**Assets deprived: no car and fewer than on "small asset"**|66.6|47.4|
|**Water deprived: no access to piped or protected source of drinking water**|45.8|50.7|
|**Distributions of individuals**|||
|Not deprived in s**c**hool, water or assets|10.3|20.1|
|Only school deprived|8.9|7.5|
|Only water deprived|4.7|14.4|
|Only assets deprived|17.3|15.1|
|School and water deprived|9.5|10.7|
|Water and assets deprived|12.5|15.9|
|School and assets deprived|17.6|6.6|
|School, water and assets deprived|19.1|9.8|

Source: HBS 2001 and 2007. Reproduced from Atkinson and Lugo (2010), "Growth, poverty and distribution in Tanzania". International Growth Centre, Working Paper 10/0831. November. Page 15. Note: small assets include television, radio, telephone (including mobile phones), refrigerator bicycle, and motorcycle.

The implication of these results for assessing the progress of the country between the two years is clear: “If it were decided that access to water were the sole concern, then deprivation would have increased from 46 per cent in 2001 to 51 per cent in 2007. *...+ *If instead, one wanted to] assess overall performance simply in terms of the proportion deprived on all dimensions *...+ this proportion has fallen, indicating definite progress.” (Atkinson and Lugo, 2010, p. 15) An effective way of presenting this kind of information on the degree of overlap across dimension-specific deprivations diagrammatically is through Venn diagrams, as Atkinson et al (2010) do for the European Union-27 countries. The larger the overlap between deprivations, the greater is the extent of interdependence. Figure 2 below (reprinted from Atkinson et al, 2010) shows the number of people that are at risk of poverty (EU definition), the number of people that are materially deprived, and the number of people aged 0-59 living in `jobless’
proximity from one another could affect their FDI attractiveness. Similar to past studies, the interest of this type of research is to provide some empirical guidance to local policymakers to help them overcome some of the obstacles that regions are facing in attracting FDI inflows.

The empirical analysis presented in the next section will be divided into interrelated parts. We investigate in the first part the significance of some of the determining factors of FDI inflows to various governorates of the country. This analysis is complemented in the second part by a spatial analysis of the distribution of the FDI across various regions and potential agglomeration and spillover effects.

# **4. 1. Presentation of variables**

In line with past research, the dependent variable in our model is the FDI which measures the inflows in millions of Tunisian dinars of incoming foreign direct investments to each governorate over the period 2008-2018 (FIPA 2019, 2017, 2016, 2015, 2014).

The potential determinants of these inflows are captured by the following economic and institutional factors:

- _Unemployment rate by governorate_ : The abundance of human resources in a region is often considered as key incentives for foreign investors who are looking for low production costs and skilled labor force (INS 2019, ITCEQ 2016, ONEQ 2013).

- _Regional GDP_ : This variable captures the productive capacity of a region. In the absence of data on regional GDP in Tunisia, we decided to use as a proxy, the regional share of consumption of high and medium voltage electricity (INS 2019, 2016).

- _Number of private companies per governorate (EPV)_ : This indicator reflects the density and dynamic of the local industrial network. Foreign actors may choose to invest in a region to leverage new business relationships, to get closer to sources of raw materials and/or to have rapid access to the services and resources necessary for production (INS 2019, 2016, 2013).

- _Number of regional development zones (ZDR):_ To attract foreign investors and promote the industrial development of certain regions, the government provides companies that choose to establish their businesses in these zones with specific incentives in the form of tax and financial incentives such as: tax exemption, investment premium, or payment of the employer's social security contribution (FIPA, 2019).

- _Governance, participatory approach and institutional quality (GOV):_ This variable is measured by an index derived from qualitative and quantitative surveys carried out by the Arab Institute of Heads of Companies in Tunisia (IACE). Several indicators measuring different aspects of good governance are taken into account, such as: the quality of municipal regulations and administrative services, the quality of
# **A Multiple Correspondence Analysis Approach to the Measurement of Multidimensional Poverty in Morocco, 2001-2007**<sup>**1**</sup>

_Abdeljaouad Ezzrari_<sup>_2_</sup> _and Paolo Verme_<sup>_3_</sup>

**JEL** : I32, O12

**Keywords** : Multidimensional poverty, Morocco, Multiple Correspondence Analysis Sector Board: Poverty (POV)

> 1 The authors are grateful to Florent Bresson and Valérie Berenger for very useful comments. 2 Observatory for Living Standards Conditions, High Commission for the Plan, Morocco 3

> The World Bank and Department of Economics, University of Turin.
_6_

# **_Physical_** _constraInts to_ **_growth?_**

_Where_ **_does_** _thls_ **_dlscussion lead me on this_** _sort of physical constralnts_ **_to growth?_** _Most of them, I thlnk, have probably been overplayed. I._ **_is_** _typical of periods of slowdown and of recession to suggest that structural dlfficulties,_ **_rigidities_** _and shortcomings have beset the world economy. That was sald durlng the so-called Great Depression of the '70s and '80s of the last century. It was deflnitely sald In the 1930s. Everybody kept arguing that in no way could we ever get out of slow growth. It_ **_Is_** _being argued again in the 1980s._ _I would have thought that both the experience of those few countries which gre,. rapidly In the course of the '30s_ **_as_** _they changed their policies, as well as the experiences of the_ **_'50s_** _and '60s suggest that these fears are not fully justified. Nonetheless there may be some truth to some of these fears and hence there may be a need for caution in any stlmulation of_ **_activity_** _or in any system shock which we may want to impart to_ **_the_** _system. But I don't think the case_ **_is_** _that important and that strong_ **_as_** _a lot of contemporary orthodoxy would lead one to believe._ _If one assumes that the supply potential_ **_Is_** _there, at least for a rate above the 2-1/2 percent which we have been experiencing_ **_for_** _a long time, say, 3 co 3.5 percent, Ideally 4, how can we_ **_get_** _to it? Now one problem is the physical capacity. The next problem is: What sort of either policies or other events can get us back to relatively rapid growth?_ _One idea, of course, would be just a return to Xeyneslanstimulated policies. I see there a much more Important constraint, not a physical one, but in a sense one of attitudes. Keynesian pollcies now are surrounded by a very large degree of skepticism. People don't believe in their efficacy. Even when their efficacy to my mind_ **_is_** _supported by both British and Japanese experience in 198688 period, nonetheless there is profound skepticism about them; hence, the chances of regenerating activity just by returning to more expansionary policies, larger budget deficits and so on, are very limited._ _Another possibility -- and thls now goes back to the transition phase itself --_ **_is_** _an orderly transition from the present problems. If we can get out of the present mess possibly in a cooperative fashion (i.e., a gradual and orderly unfolding of the global payments imbalances) combined with a much higher degree of optimism, we could generate the system shock which to my mind is essential for a return to high growth._ _In other words, just as growth in the 1950s and 1960s was very rapid, thanks partly (or largely to my mind) to a regime change, a move from basically laissez-faire government policies to much more interventionist in the macroeconomic field by government policies, a regime change could occur in the late 1980s where we move from basic._

**WP/PROCISF:Jsq**
cross-listing or through issue of American Depository Receipts and General Depository Receipts. Within Africa, the Johannesburg Stock Exchange will most likely be the only stock market able to sustain sufficient scale in the years to come, and even that only in cooperation with stock exchanges in Europe and North America. On the other hand, there is a need to mobilize longterm resources locally—for example, for infrastructure projects—which will require a comprehensive policy package, including pension reform.

Although not documented in a statistical sense, there seems to have been progress in expanding outreach as well. Technological advances have allowed Sub-Saharan Africa to leapfrog, as, for instance, in utilizing mobile telephone technology for expanding the share of population having access to payment services, as the example of M-Pesa in Kenya has shown. Banks across the region are offering innovative financial and low-cost products and utilize new technologies to reach out to larger shares of the population (Box 1). As we will discuss below, changes in market structure seem to have resulted in more innovative marketplaces in several countries, with a number of banks attempting new ways and products to expand outreach.

# **Box 1: The impact of the financial crisis on Africa**

Although the direct impact of the current crisis in the United States and Europe on African financial systems is relatively contained—given that African banks are not as closely integrated in the global financial system as other regions of the developing world and hold most of their assets and commitments on rather than off the balance sheet—indirect effects through the real economy and through reduced private capital inflows caused by reduced risk appetite might very well have negative repercussions for real and financial sectors in Africa.

African banks are, on average, not exposed to risks arising from complex derivative instruments or products. They have typically low loan-deposit ratios and high liquidity reserves. Unlike in several European countries—and with the notable exception of South Africa—there is also very limited 9