rafmacalaba/datause-encoder-data huggingface dataset:
repairs and maintenance. The average savings for households are about 10.4% of their total monthly income and 50% of the total savings are kept in the bank account. However, from 34 households in BPL category, 20 families (60%) are not able to save anything from monthly incomes. From the remaining 14 families, only 6 have reported keeping savings in bank accounts and that amount is about 20% of total savings. This is an important finding and highlights how vulnerable the incomeexpenditure portfolio of the poor people is and how flood impacts would adversely affect this portfolio. A recent World Bank report,<sup>31</sup> using the global database, shows how poor people have no savings in financial form such as bank deposits than their better-off counterparts. The case study of Colombo shows, in actual numbers, how families in the BPL category are more vulnerable to natural hazards on account of extremely limited financial assets.

Besides monthly income and expenditure, information on the ownership of different appliances, assets and vehicles has been obtained to understand more about the socioeconomic profile of these households. Percentage of ownership among different categories of households along with average cost of appliances and vehicles is given in Table 4 below. The ownership pattern differs significantly across three categories. Majority BPL families have cellphones, LPG, television and electric fan. But their ownership of high-end consumer durables like refrigerators, washing machines and air conditioners is almost negligible. Even for the poor families, ownership of such appliances is considerably lower compared to families in the non-poor category. Even in the case of vehicle ownership, BPL households do not own a car. Car ownership is 5.8% and 27.9% of households among poor and non-poor families, respectively. 24.4% of families among the poor own an auto rickshaw that provides their livelihood.

_Table 4: Ownership and average cost of household appliances and vehicles_

|**Appliance**|**% o**<br>|**f ownersh**<br>|**ip**<br>|**Average cost**<br>**of appliance**<br>**(LKR)**|
|---|---|---|---|---|
||BPL|Poor|Non-poor||
|LPG|73.5|82.7|97.7|4,500|
|Electric fan|67.6|94.2|100.0|6,000|
|Television|73.5|92.5|97.7|25,000|
|DVD|17.6|51.4|76.7|2,000|
|Music<br>system|44.1|31.2|18.6|11,600|
|Refrigerator|17.6|58.4|93.0|15,000|
|Washing<br>machine|5.9|20.2|76.7|36,300|
|Air<br>conditioner|0.0|2.3|9.3|72,000|

> 31 Hallegatte et. al. (2017), Unbreakable: Building the resilience of the poor in the face of natural disasters, Climate Change and Development Series, Washington DC, World Bank, doi:10.1596/978-1-4648-1003-9.

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capital, especially public infrastructure and administrative capacity, while building human resources through greater education spending. Investing in produced and human capital will help to lay the foundation for enhanced competitiveness while promoting positive spillover effects from the high levels of FDI flowing into the country. However, if negative ANS rates persist, Mauritania’s national wealth stocks will continue to be depleted, and its current growth may ultimately prove unsustainable over the long term.

# Policy Implications

## **IN A CONTEXT OF NEGATIVE ANS OVER GNI, MAURITANIA NEEDS TO RECALIBRATE NATURALRESOURCE WEALTH MANAGEMENT TO BUILD THE FOUNDATION FOR LONG-TERM GROWTH**

**Sustainable growth is defined as “growth that meets the needs of the present without compromising the ability of future generations to meet their own needs”**<sup>**42**</sup> **.** A country that grows rapidly on the strength of nonrenewable resources without rebuilding its stock of wealth by investing in other forms of capital will not be able to maintain its growth over the long term, and risks sacrificing the wealth of future generations to finance its current consumption. A sustainable growth strategy must account for the temporal and intergenerational dimensions of resource wealth by ensuring that current growth does not come at the expense of future growth. Clearly, the discovery of new forms of extractive resources can also play a positive role.

**Looking at the macroeconomic and fiscal environment, the core question is whether the consumption/savings balance is adequate and if not what could be done about it.** Adopting policies aimed at increasing savings and maximizing rents from natural resources, sustaining human capital investment, adopting transparent and consistent fiscal policies will be vital to building the government’s policy credibility and expanding the available space for public investment or free-up resources to build fiscal reserves. Authorities are aware of the need to diversify the economy, boost competitiveness and private-sector confident, and promote progressive increases in domestic value addition to create jobs and make growth more than merely selling off raw commodities. These objectives have become more pressing in recent years, as a food crisis from 2011-2012 and by the sociopolitical instability of the Sahel region have underscored the importance of broad-based poverty reduction. The primary objectives of the government’s latest Poverty Reduction Strategy Paper ( _Cadre Stratégique de Lutte contre la Pauvreté_ ) for 2011-2015, as well as the World Bank’s Country Partnership Strategy for 2013-2017 and complementary medium- and long-term development strategies focus on economic diversification, poverty reduction and job creation.

> 42 Quote from World Commission on Environment and Development’s (Brundtland Commission) report “Our Common Future”, Oxford: Oxford University Press, 1987

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in Ethiopia (Mascagni and Molla 2018). It is unclear if a similar pattern would be observed around the presumptive tax exemption threshold.

The design of a tax on small and microenterprises needs to consider the tradeoffs between bringing informal businesses into the tax net and the administrative costs (Keen and Mintz 2004). These considerations are particularly important for microenterprises because of their limited revenue generation potential. While medium-sized firms may benefit from tax registration by increasing their customer base and sales, micro-level businesses may not reap the benefits of formalization (see Benhassine et al. 2018 and McKenzie and Sakho 2010 for examples from Benin and Bolivia, respectively). Tax administrations’ capacity in terms of resources and skills may also be limited to monitor and collect taxes from microenterprises.

# **7. Conclusion**

This paper examines the equity and gender implications of the presumptive tax on small and microenterprises. Using nationally representative household data and the tax code, the findings show that the tax burden is borne most heavily by the smallest enterprises, thereby making it regressive. The smallest male-owned businesses face a higher effective tax rate compared to female-owned businesses because a larger share of male-owned businesses operate in sectors without an exemption threshold. The results also show that businesses in the food and beverage service subsector, which are predominantly female-owned, and the transit service subsector, which are predominantly male-owned, face a high tax burden because of the lack of a tax-free threshold for these subsectors. Such high tax rates for small enterprises could discourage entrepreneurs from registering their business for taxation and threaten the business sustainability.

The presumptive taxation on small and microenterprises in Ethiopia consists of different tax rates for 99 business sectors with 19 turnover bands (with a total of 1,881 activity-bands). The complexity of the tax schedule and the existing process of estimating tax liabilities using daily revenue to extrapolate annual revenues have led to discontent among taxpayers, which could undermine trust towards tax authorities and the perception of tax fairness. An alternative presumptive tax system that is assessed on a fixed percentage on turnover and exempts low revenue firms would reduce the regressivity and promote equity and simplicity.

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immigrants’ returns as the difference between the initial inflow of a cohort arrived in year _t_ and the stock remaining at a later date _t_ + _k_ . Following OECD (2008), we identify a cohort size entering at year _t_ on the basis of respondents present in the ACS data in year _t_ + 1 and reporting to have arrived in the preceding year. We then use the ACS in year _t_ + _k_ to identify migrants who entered in year _t_ and are still present in _t_ + _k_ . To reduce statistical noise due to the small sample size of the ACS (1 percent of the population), we group together cohorts arriving between 2007 and 2012 and examine their return migration up to 9 years after migration (e.g., until 2021 for the 2012 cohort and until 2016 for the 2007 cohort). As with the analysis in section 4.1, we focus on individuals who migrated from a developing country and moved when they were adults between 18 and 40.

Figure 3 shows that migrants married before migration are more likely to return to their home country compared to migrants unmarried before migration: 24 percent of initially married migrants have returned after 9 years, compared to 14 percent for those who migrated unmarried. This is true both among men and women, with the former being more likely to return than the latter (34.9 percent of initially married men have returned after 9 years compared to 14.2 percent of initially married women).<sup>20</sup> Note that this form of selection into return migration by initial marital status makes only a marginal difference to our Table 1 finding that a majority (55.9 percent) of migrants are unmarried before migrating. In fact, for migrants who report to have arrived in the U.S. within one year (and hence are unlikely to have already returned home), this share stands at 52.9 pecent, and it is relatively stable over the years since migration (58.3 percent after nine years or more).<sup>21</sup> Figure 4 then examines how sensitive our Figure 2 results on the likelihood of a change in marital status after migration are to accounting for return migration. It displays both the probabilities of changes conditional on staying in the U.S., and our lower bounds on the unconditional changes, assuming no change in marital status after return migration. For migrant men who were unmarried before migration, the probability to get married nine

> 20Due to sampling noise, we obtain a slightly negative rate of return migration for some years. When we examine immigrants from all origin countries, we obtain an overall rate of return migration of 23 percent nine years after migration, consistent with previous studies’ estimates (OECD, 2008; Borjas and Bratsberg, 1996).

> 21These figures are obtained using the 2017-2021 ACS data (as in Table 1). Using the 2008-2021 ACS data and focusing on the 2007-2012 cohort, we obtain a share of unmarried migrants of 57.8 percent for migrants arrived one year ago or less and of 60.6 percent for migrants arrived since nine years.

21
men are more likely to own property than women. Even after controlling for demographic and other factors a substantial gender gap in ownership persists. The disadvantage in property ownership experienced by women reflects a variety of factors, most importantly discriminatory norms and laws with respect to inheritance and marital regimes. Lower ownership among women also limits their bargaining power within marriage and fallback options on dissolution of marriage or on death of the husband.

The DHS data on ownership of land and housing at the individual-level are a substantial improvement over previous rounds, where such data were collected only at the household-level, and have allowed us to explore descriptive patterns of male and female property ownership. But information only on the incidence of ownership is restrictive in determining the causes and consequences of gender property gaps. Data on modes of acquisition of property, different notions of ownership and rights over assets, and value of assets are needed to improve our understanding about gender gaps. Information on how assets are acquired by both men and women would help in understanding where the gaps originate from and why these persist. Data on various notions of ownership – perceived, legal and rights-based – would provide for a better understanding of what asset ownership means for the individual and to explore the concept of joint ownership. Individuals might not be legal owners of property, but still enjoy decision-making power over how the property is used or to whom it is bequeathed. Incidence data, being of binary nature, also restricts the analysis of inequality in asset ownership and polarization. Data on the value of assets owned would be useful to assess differences between men and women in property wealth. Emerging best-practice standards (e.g. Doss et al 2008, 2013, 2017) for the collection of individual-level data on ownership, use and control of assets are an important milestone towards advancing this data collection and analytic agenda.

26
**_Figure 6_**

_Nominal Maize Prices, Dar es Salaam and Nairobi_ <!-- Start of picture text --> TZ Shillings/kg<br>1,000<br>Dar es Salaam Nairobi<br>800<br>600<br>400<br>200<br>0<br>Jul-02 Jul-03 Jul-04 Jul-05 Jul-06 Jul-07 Jul-08 Jul-09 Jul-10 Jul-11 Jul-12 Jul-13 Jul-14<br><!-- End of picture text -->

**Source** : Ministry of Industry and Trade, Tanzania

**_Figure 7_**

_Nominal Maize Prices, Domestic Comparison_ <!-- Start of picture text --> TZ Shillings/kg<br>1,000<br>Songea Dar es Salaam Mwanza<br>800<br>600<br>400<br>200<br>0<br>Jul-02 Jul-03 Jul-04 Jul-05 Jul-06 Jul-07 Jul-08 Jul-09 Jul-10 Jul-11 Jul-12 Jul-13 Jul-14<br><!-- End of picture text -->

**Source** : Ministry of Industry and Trade, Tanzania

36
also interpret this interaction in the view of recent research that has shown the negative impact of inflation on financial sector development (Boyd, Levine, and Smith, 2001). This interpretation would characterize inflation volatility as decreasing the ability of financial intermediaries to serve as shock absorber and thus its capacity to reduce growth volatility. However, the insignificance of Private Credit in the regression without interaction terms and the joint insignificance of Private Credit and its interaction terms in Tables 5 and 6 are counter to this interpretation.

# **5. Concluding Remarks**

This paper (i) assessed the impact of financial intermediary development on growth volatility and (ii) explored potential channels through which these two variables might be linked. In our theoretical model financial intermediaries arise to alleviate agency costs and cash flow constraints on entrepreneurs and thus dampen the impact of real shocks. At the same time, financial intermediaries serve as conduit for monetary policy propagation into the real economy. Our theoretical model thus predicts a dampening effect of financial intermediaries on the propagation of real shocks and a magnifying effect on the propagation of monetary shocks. Depending on the shocks an economy is exposed to and the relative size of these shocks, financial intermediaries might therefore have an overall dampening or amplifying impact on growth volatility. Our empirical analysis of 63 countries over the period 1960-97 confirms this prediction and does not show any significant impact of financial intermediaries on growth volatility. Further, we find only weak evidence for a dampening role of financial intermediaries in the propagation of terms of trade shocks. However, we find a magnifying role of 28
When examining the female sample and male sample separately, it is found that the earnings premium for SMK graduates is only significant for the male sample. However, after using Heckman’s 2-step procedure to correct the sample selection bias, this male SMK wage premium becomes insignificant (Table 5).

**Table 5: Regression of EARNINGS (in IDR) in 2000 (IFLS3, n=252, 515, 128, 258, 124 & 257), with and without censoring correction**

||All||Female||Male||
|---|---|---|---|---|---|---|
|Indeendent|OLS|Heckman|OLS|Heckman|Selection|Heckman|
|p<br>variable|coefficient|2-step|coefficient|2-step|equation|2-step|
||estimates|estimates|estimates|estimates|estimates|estimates|
|RURAL|-549,218*|-558,768*|-614,066*|-635,735*|-479,310|-370,741|
||(285,538)|(321,134)|(355,545)|(376,951)|(458,486)|(555,599)|
|FEMALE|144,960|143,284|||||
||(271,750)|(269,855)|||||
|AGE|378,989.***|375,070***|552,753***|541,741***|204,897|238,110|
||(105,758)|(121,991)|(132,641)|(149,049)|(166,637)|(191,663)|
|SMK|576,895**|564,774*|371,828|353,463.|772,357*|931,816|
||(273,775)|(333,286)|(341,856)|(356,563)|(439,088)|(643,329)|
|EBTANAS1|52,526**|53,763*|77,296**|80,018**|20,809|8,156|
||(25,214)|(31,871)|(29,836)|(34,340)|(42,734)|(56,494)|
|Intercept|-<br>7,320,112***|-<br>7,243,430***|-1.1e+07***|-1.1e+07***|-2,948,517|-3,576,034|
||(2,431,150)|(2,699,510)|(2,998,174)|(3,297,283)|(3,862,292)|(4,236,634)|
|Mills ratio||-44,246||-121,374||399,596|
|||(710,669)||(801,548)||(1193612)|
|_Chi_<sup>_2_</sup>||78.82||40.11||50.25|
|_Rho:_||-0.021||-0.065||0.174|

15
adopts the official exchange rate in the current account conversion; whereas the tourism and services sector might resort to the parallel exchange rate market The following matrix summarizes the short term dynamics within the system:

**Independent Variables** DDexrt Dexrt Dexrt DDexrt DInterest Drm2_1 Drm2_2 DINFL DINFL_1 end_1 prmium prmium_1 end_1 rt_1 Drm2 **+ + - + -** Drgdp **+ + + - -**

The discount rate responds positively to the lagged real money balances. It can also be perceived as a shock absorber to the 1991 IMF structural adjustment program that lead to raising the average discount rate by 4 percent as part of the monetary tightening plan and fighting dollarization. It was hiked by 3 percent in 2008 to defend the domestic currency and rebuild trust in the Egyptian pound in the aftermath of the global financial crises. Finally, the model captures a drop of 2.7 percent in 2012 as a reaction to the attempt to relax monetary policy to expedite a post 2011 revolution economic recovery. It is also seen as a source of disequilibrium in the system and a deviation of 0.24 percent off the stay state for a 1 percent increase in the discount rate.

# **_8.  Conclusion_**

The money demand equation for Egypt is stable under both closed and open economy formulations. The monetary authority can resort to monetary aggregates to achieve monetary policy objectives and adjust for long run growth in the real economy.

The money income elasticity under an open economy formulation remained within acceptable norms of 1.3 and is statistically not equal to unity. This is due to the fact that the increase in real income in the economy is coupled with an uptrend in monetization as the ratio of money stock over output is uptrending.

One key finding of this research confirms that the adjustment of real money to disequilibrium in the short term is slow. This might be attributed to structural factors related to financial underdevelopment and stagnant wages and prices. The Egyptian economy has undergone massive transformation during the past five decades, yet exhibited low employment levels and strong inflation inertia. Moreover, domestic inflation has a weakly exogenous characteristic in the money 38
|2003/04|89|200,000|43|89,859|165,000|
|---|---|---|---|---|---|
|2004/05|32|200,000|9|15,123|15,123|
|2005/06|32|150,000|21|34,942|34,942|
|2006/07|58|150,000|10|27,641|27,641|
|2007/08|10|150,000|10|26,843|26,843|
|2008/09|10|150,000|10|8,804|10,915|
|2009/10|10|150,000|10|21,500|32,231|
|2010/11|15||9|11,400|11,400|

_Source: MCDSS_ However, due to funding constraints the program never managed to reach 200,000 in any single year of its first five years of operation. Furthermore, the number of beneficiaries fell drastically after its peak in 2003/04. The inadequate funding and unrealistically high beneficiary targets set by the government frequently resulted in the provision of incomplete packs and/or the splitting of packs between farmers. For instance, between 2001 and 2004 beneficiaries received incomplete packs consisting of 0.25 hectares worth of maize seed, 0.125 hectares of legumes and 0.03125 hectares of tubers. For the 2004/2005 season, the input pack size was increased to cover 0.5 hectares of cereal instead of the standard 0.25.

One notable difference between the FSP and FISP programs is that the former has been able to graduate significant numbers of beneficiaries. Since the 2005/2006 agricultural season the FSP pack has been largely provided to new beneficiaries only.

# **4. Data Sources and Allocation of Benefits**

# **4.1. Data Sources**

The empirical analysis presented below is based on the Living Conditions Monitoring Survey of 2010 (LCMS VI), which was designed to monitor the impact of the Fifth National Development Plan (20062010) and to constitute a baseline for the Sixth National Development Plan (2011-2015).<sup>14</sup> The survey includes modules covering health, education, economic activities, household expenditures and household agricultural production. The LCMS VI is a nationwide survey covering both rural and urban areas in all nine provinces. The survey includes representative samples for each of Zambia‘s 72 districts. The total

> 14 Both plans are part of a series of medium-term strategies with the objective of ―making Zambia a prosperous middle-income country by 2030‖ (Government of the Republic of Zambia, 2011).

16
instance, let _P_ 1 ( _xM_ ) and _P_ 1 ( _x F_ ) be the MPIs for men and women, respectively. The gender difference _GD_ = _P_ 1 ( _xM_ ) − _P_ 1 ( _x F_ ) could be expressed as follows: It is then easy to compute the contribution as a percentage of each dimension to the gender difference as follows:

# **_3.4 Data_**

The CWIQ 2011 is used for Togo, while the data for Burkina Faso come from EICVM 2009/2010. Both surveys are stratified two-stage designs and are nationally representative. The EICVM is conducted in four stages, but only the first stage is used by the present study. After data clearance, 8,421 households are retained out of the 9,075 households initially included in the sample. Regarding the CWIQ, 6,048 households are included in the initial sample.

Individuals aged 15 to 64 years are the unit of analysis. In the case of Burkina Faso, the final sample includes all individuals, which represents 26,124 people from 8,258 households, including 11,698 men (45%) and 14,426 women (55%). Also, 27% of people are urban while 73% live in rural areas. By contrast, in Togo, only the household head and his spouses are considered for the question involving financial resources. This leads to retaining 8,229 individuals from 4,980 households, for 3,716 men (45%) and 4,513 women (55%). This large sample drop may introduce a bias in the short sample. In fact, some socio-demographic features (e.g. average household size and average age) appear significantly different from one sample to another. Moreover, this country appears more urbanized than the previous one since urban represents 42% against 58% for rural.

18