rafmacalaba/datause-encoder-data huggingface dataset:
# **7. References**

Akter, Sonia, Pieter Rutsaert, Joyce Luis, Nyo Me Htwe, Su Su San, Budi Raharjo, and Arlyna Pustika. 2017. "Women's empowerment and gender equity in agriculture: A different perspective from Southeast Asia." _Food Policy_ 69: 270-279 Alkire, Sabina, Ruth Meinzen-Dick, Amber Peterman, Agnes Quisumbing, Greg Seymour, and Ana Vaz. 2013. “The Women’s Empowerment in Agriculture Index”. _World Development_ 52: 71-91 Allendorf, Keera. 2007. “Do Women’s Land Rights Promote Empowerment and Child Health in Nepal?” _World Development_ 35(11): 1975-1988 Alwang, Jeffrey, Catherine Larochelle, and Victor Barrera. 2017. "Farm Decision-making and Gender: Results from a Randomized Experiment in Ecuador." _World Development_ 92(4): 117-129 Ambler, Kate, Cheryl Doss, Caitlin Kieran, and Simone Passarelli. 2021. “He Says, She Says: Spousal Disagreement in Survey Measures of Bargaining Power.” _Economic Development and Cultural Change_ 69(2): 1-24 Amugsi, Dickson, Anna Lartey, Elizabeth Kimani-Murage and Blessing U. Mberu. 2016. “Women’s participation in household decision-making and higher dietary diversity: findings from nationally representative data from Ghana”. _Journal of Health, Population & Nutrition_ 35(1) Anderson, C. Leigh, Travis W. Reynolds, and Mary Kay Gugerty. 2017. "Husband and Wife Responses on Farm Household Decision-making Authority and Evidence on Intra-household Accord in Rural Tanzania." _World Development_ 90(2): 169-183 <mark>Annan, Jeannie, Aletheia Donald, Markus Goldstein, Paula Gonzalez Martinez, and Gayatri Koolwal. "Taking power: women’s empowerment and household well-being in Sub-Saharan Africa."</mark> _<mark>World Development</mark>_ <mark>140 (2021): 105292.</mark> <mark>Arugay, Aries, Forest Jarvis, Hillary C. Johnson, Sundas Liaqat, and Aletheia K. Valenciano. 2021.</mark> _<mark>Understanding the gender dynamics of decision-making in agrarian households of the rural Philippines.</mark>_ <mark>Washington D.C.: World Bank</mark> <mark>Arugay, Aries, Aletheia Donald, Forest Jarvis, Hillary C. Johnson and Aletheia K. Valenciano. Forthcoming.</mark> _<mark>Authority by choice: Unpacking the links between decision-making and autonomy in the rural Philippines.</mark>_ <mark>Washington D.C.: World Bank</mark> Bankole, Akinrinola, and Susheela Singh. 1999. "Couples' Fertility and Contraceptive Decision-making in Developing Countries: Hearing the Man's Voice." _International Perspectives on Sexual and Reproductive Health_ 24(1): 15-24 Bayudan-Dacuycuy, Connie. 2011. "The Influence of Living with Parents on Women's Decision-making Participation in the Household: Evidence from the Southern Philippines." _The Journal of Development Studies_ 49(5): 641-656 Brinkerhoff, Megan & Eugen Lupri. 1978. "Theoretical and methodological issues in the use of decisionmaking as an indicator of conjugal power: some Canadian observations." _Canadian Journal of Sociology_ 3 (1): 1- 20 27
**Table 8: Supply of rice to the Sierra Leone market (2009 – 2018)**

|**Year**|**Total Supply**|**Domestic**<br>**Production**|**Imp**|**orts**<br>|
|---|---|---|---|---|
||_Volume(Mt.)_|_Volume(Mt.)_|_Volume(Mt.)_|_Value(US$’000)_|
|2009|698,840|592,570|106,270|45,169.00|
|2010|685,569|616,003|103,500|43,950.00|
|2011|833,011|677,603|155,408|84,726.48|
|2012|941,906|684,850|257,056|111,395.54|
|2013|1,085,819|753,335|332,484|129,385.30|
|2014|897,066|489,908|407,158|120,719.50|
|2015|917,560|597,216|320,344|141,490.03|
|2016|1,029,709|695,255|334,454|96,886.67|
|2017|1,149,547|538,241|611,306|191,380.19|
|2018|959,513|551,751|407,762|120,083.47|

Source: Based on data from Ministry of Agriculture and Food Security and Bank of Sierra Leone

# _Rice price_

Government's policies with respect to the incentive framework have had a serious negative effect on agricultural production. The overvalued leone imposed low producer prices for rice, since imports at the low rate of exchange depressed the domestic urban market price. The price of rice in the retail market in 2016 was Le4,887.05 per kilogram.<sup>13</sup> This is equivalent US$769.76 per ton based on the exchange rate of Le6348.79 per US$ in 2016. The world price of US$396 per ton and the implicit average cif price of US$289.68 calculated from Table 8 would suggest that the mark-up on rice to the final consumer is substantial—more than a doubling. However, since the price of imported rice is variable over the months, reaching and average cif of US$440.34 between June and December 2016, it is assumed that the risk averse, profit-maximizing importer/distributer would base the final price on the US$440.4 cif price rather than the lower US$289.68 per ton. The average price of rice increased to Le12,831 per kilogram in 2018, in large part because of the substantial depreciation of the leone, as the world market price increased by only about 2 percent between 2016 and 2018. With the exchange rate of Le 7,393.57 per US dollar the 2018 retail price amounts to Le 4,877 per kilogram or US$660 per metric ton.

The reference or border price of imported rice used in the model is given algebraically as: Pb = (Pw + Tw) + Td - Cb; and the export border price is given as: Pb = Pw - Tw - Td - Cb Where: Pb is the reference price at the farm gate; Pw is the world price; Tw is the shipping and insurance charges; Pw +Tw represents the CIF price at the domestic port;

> 13 Based on the CPI survey conducted by Statistics Sierra Leone.

17
68

# Table 14

Czech Legal Workers in West Germany* and in the Bavarian Border Regions

||1990|1991|1992|1993|
|---|---|---|---|---|
|Czech workers in West Germany<br>Index base 1990<br>As % of the total LF<br>As % of all foreigners|13394<br>100<br>0.06<br>0.75|20927<br>156<br>0.09<br>1.10|32258<br>241<br>0.14<br>1.58|34064<br>254<br>0.15<br>1.56|
|Czech in Bavarian border regions<br>Index base 1990<br>As % of the total LF<br>As % of all foreigners|502<br>100<br>0.1<br>2.8|5871<br>1170<br>0.9<br>22.8|13172<br>2624<br>2.1<br>37.8|12980<br>2586<br>2.1<br>35.1|
|% of all Czechs in WG|3.7|28.1|40.8|38.1|
|Memorandum values|||||
|West German LF<br>Index base 1990 total<br>of which|22368078<br>100|23173439<br>104|23530259<br>105|23122456<br>103|
|Index base 1990 Germans|92|95|96|93|
|Index base 1990 foreigners|8|9|9|10|
|<br>Share of foreigners in the LF in WG|8.0|8.2|8.7|9.4|
|BBR LF<br>Index base 1990 total<br>of which|596165<br>100|628424<br>105|638665<br>107|629660<br>106|
|Index base 1990 Germans<br>Index base 1990 foreigners|97<br>3|101<br>4|101<br>6|100<br>6|
|<br>Share of foreigners in the LF in BBR|3.0|4.1|5.5|5.9|
|Czechs in "Werksvertrag" in WG||6348**|11646**|595**|
|BBR LF as Share of WG LF (%)|2.7|2.7|2.7|2.7|

*Note: Employment statistics are only available for the old Federal Republic.

_**Note:_ Stocks for Werksvertrag-employees are end-of-year. All other stocks are mid-year. Source: Beschaftigtenstatistik der Bundesanstalt fur Arbeit, Nuremberg.
# _3.1 Construction of the pre-simulation database_

On the eve of the Arab Spring, the Levant economies were eager to move forward with plans for a new Levant Economic Zone (LEZ) which would have enforced deep trade concessions and therefore generated potentially bigger gains than those associated with past shallow trade agreements.<sup>5</sup> It would have removed tariffs on agricultural and processed foods trade between Turkey and the five Levant countries and would have liberalized transport and trade in other services within the LEZ. Reforms were expected to address the constraints to a strong supply response by reducing the negative effect of public monopolies in key services sectors,<sup>6</sup> harmonizing business and investment climate rules and regulations,<sup>7</sup> especially those governing investments in services, improving domestic and cross-border infrastructure and logistics and the implementation capacity in junior partner countries.<sup>8</sup> The hope was that reforms would propel convergence toward best practices and thus advance private sector development in the greater Levant area.

Importantly, the regional trade agreement would have underpinned political and security arrangements in the region, consolidated the bilateral FTAs of Egypt, Lebanon, Jordan, and Syria with Turkey, and improved market access for Turkey and Iraq to each other’s economies. The negotiations were expected to be constrained by Turkey’s pre-existing agreements. Turkey

> 5 In MENA, the benefits of trade liberalization, involving mainly tariff removal on manufactured goods, have been limited (Testas, 1998, 2002; Al-Atrash and Yousef, 2000; and Freund and Portugal-Perez, 2012). Konan (2003) and Bchir et al. (2006) argued that the benefits would increase with deepening of the commitments, especially the opening of the services sectors. Barriers to trade in services were higher than in economies with similar incomes in other parts of the world (Hoekman and Sekkat, 2010) and their removal was expected to lead to a significant productivity boost in services and the boarder economy (Hoekman and Messerin 2001).

> 6 See, for example, studies by Hoekman and Zarrouk (2000) and Rosotto, Sekkat, and Varoudakis (2005).

> 7 Using a survey of firms in eight Arab countries, Zarrouk (2003) estimated that in 2000 the cost of getting goods across borders was on average 10 percent of the value of transported cargo. Prohibitions, arbitrary changes in documentary requirements, surcharges, and discriminatory taxes imposed severe costs on intra-Arab trade.

> 8 Recent assessments suggest that progress has been made in terms of reducing the frequency and restrictive power of non-tariff measures (NTMs) (Augier et al. 2012).

12
The implications for standard models of tax evasion and regulatory compliance are straightforward. Traditional approaches assume that enforcement agencies try to maximize social benefit (minimize social harm) subject to a binding budget constraint. Both these approaches and ours predict that large firms (the biggest violators on a per unit output basis) are more likely to participate. The difference between approaches lies in the determinants of compliance: traditional approaches assume that enforcement solely determines compliance; we model the (relative) net benefit to the firm. The actual importance of gross benefits versus gross (penalty) costs is an empirical matter, one that, unfortunately, we cannot test with our data. However, our approach shows that both costs and benefits to the firm should be accounted for when attempting to identif the importance of enforcement efforts.

Moreover, our approach indicates that the _duration_ of an economic activity should be considered when modeling participation. Traditional approaches to tax evasion and regulatory compliance typically ignore this issue, in part because they consider long-lived economic agents; in particular, firms are viewed as infinitely long-lived. However, we have shown that if firm dynamics play an important role in the economy -- as they appear to do -- then they should be factored into participation considerations.

# **III. Erapirical results**

1992 National Micro Enterprises Survey (ENAMIN) from Mexico, offers the first comprehensive survey to date on compliance with or participation in several distinct markers of formality including registration with the tax authorities, tax payment, labor protection, participation in guilds or trade associations, and enumeration in the census, as well as other relevanit characteristics. It thus, permits us to generate a reliable picture of the nature of informality, as well as to test the consistency of our framework with reality. The sample was generated by selecting approximately 11,000 individuals from the 1991:4 National Urban Employment Survey who declared that they were self-employed or heads of firms of five workers or fewer (fifteen or fewer in manufacturing). They were reinterviewed in the next quarter to generate a more detailed accounting of income, capital stock, costs, employment patterns, and a variety of details related to participation in societal institutions. Of the sample of individuals 11
Figure 3a shows the results of this exercise for eight African countries: the two most industrialized countries in Sub-Saharan Africa, Mauritius and South Africa, along with six African countries which experienced a relatively recent growth acceleration Ethiopia, Ghana, Kenya, Nigeria, Senegal and Tanzania. The only country for which UNIDO has data which has been excluded from Figure 3a is Botswana where the trend looks like that in South Africa. The vertical lines in each graph mark the start of the country-specific growth acceleration documented in Diao et al. (2021). The most striking trend in all but two of these countries is the upward-sloping curves for employment in small and informal manufacturing employment and the relatively flat lines for formal sector manufacturing employment. The patterns in Ghana, Kenya, Nigeria and Senegal are similar as those in Ethiopia and Tanzania presented in Diao et al. (2021). In short, the beginning of the rise in small/informal sector employment largely coincides with the beginning of the growth acceleration in the African countries. However, the relatively higher-income African countries South Africa and Mauritius have a different pattern. In more-developed economies, formal employment is a much higher share of total manufacturing employment—although one can see a modest surge in employment in firms with fewer than 10 employees starting in the mid-1990s in South Africa’s manufacturing sector.

Figure 3b shows starkly different patterns for four Asian late industrializers: Bangladesh, Lao PDR, Sri Lanka, and Vietnam. Again, the vertical lines represent the beginning of each countries’ growth acceleration. Unlike the African cases, formal sector manufacturing employment in these four countries grows rapidly following the growth acceleration. Over these same periods and apart from Bangladesh, employment in small and informal firms remains relatively flat and even starts to decline slightly in Vietnam after 2005: for a description of the transition in Vietnam, see McCaig and Pavcnik (2017). Like the African countries, the Asian late industrializers were largely agrarian societies before the start of their growth accelerations. Although not shown, increases in formal manufacturing employment in these countries coincided with gradual declines in agricultural employment shares. These patterns combined with the evidence in Figure 2b are consistent with the idea that structural change in these countries was a result of positive supply shocks to the manufacturing sector.

# _Employment and Labor Productivity Growth in Formal Manufacturing Firms_

The informal sector has apparently absorbed a large majority of the growth of manufacturing workers in African countries. Why aren’t formal sector manufacturing firms creating more jobs in Africa?

8
size according to the following five-category classification: _size_ = _{_ self-employed without employees, employee in a business with 1-10 employees, owner of a business with 1-10 employees, employee in a business with 10+ employees, owner of a business with 10+ employees _}_ More formally, indexing individuals by _i_ , denoting as _yi_ the ratio between the earnings distribution median and individual _i_ ’s earnings, and denoting the mean of _yi_ within a given size class as _y_ ̄ _j,D_ 1 = <u>�</u> _i∈N_ <u>(</u> _j,Dj,D_ 11)<sup>_yi_</sup> , the average median-to-own earnings gap for a given decile of the earnings distribution (D1) can be written as: where _ND_ 1 is the number of individuals in D1, and _Nj,D_ 1 is the number of individuals in category _j_ within D1. For brevity, we focus on the distribution’s extremes, analyzing deciles 1 and 10 exclusively, denoted respectively as D1 and D10. For D10, we define _yi_ as the ratio between the earnings of individual _i_ and the median of the earnings distribution (i.e., we define it inversely so that the absolute gap is always measured vis-a-vis the median).

The within term captures the average deviation from median earnings across business size categories, while the between term captures the allocation of workers across categories with larger/smaller earnings deviations from the median. Equation 1 underlines high inequality, measured by the gap between average earnings in the extreme (top or bottom) deciles and median earnings, can be explained by a large gap versus median earnings in the average size category, by the concentration of workers in categories with the largest earnings gaps, or by a combination of these. We counterpose the LATAM and U.S. results and ask to what extent greater inequality in LATAM is explained by the cross-category allocation of workers, or by earnings gaps versus the median in each category.

The first key takeaway from this decomposition is that, in LATAM, the between term contributes positively to the gap between earnings and median earnings in decile 1, increasing inequality, but diminishes that gap in decile 10. This is seen in Table 2, where we report results for the different terms of decomposition 1. Earning gaps are reported only for categories that absorb at least 0.5% of employment. The top panel of the table corresponds to LATAM, weighing country-level decompositions by the corresponding number of workers, while results for the U.S. are reported in the middle panel. Columns 1-3 show results for the bottom earnings decile, while columns 4-6 do so for decile 10. In the row marked “Total”, columns 3 and 6 report ̄ <u>�</u> _<u>j∈size</u>_<sup>_y_ ̄</sup><sup>_j,D_1</sup> _yD_ 1 (left-hand side of equation 1), while columns 2 and 5 report the within term, 5 .

The between component (residual between the two just mentioned) contributes positively to the gap between median earnings and D1 earnings in LATAM: the total gap is 10.97, of which 16
# **A Flexible Modeling Framework to Estimate Interregional Trade Patterns and Input-Output Accounts**

Patrick Canning, Economic Research Service, US Department of Agriculture Zhi Wang, World Bank and City University of Hong Kong *

## **Abstract**

This study implements and tests a mathematical programming model to estimate interregional, interindustry transaction flows in a national system of economic regions based on an interregional accounting framework and initial information of interregional shipments. A national input-output (IO) table, regional data on gross output, value-added, exports, imports and final demand at sector level are used as inputs to generate an interregional IO account that reconciles regional economic statistics and interregional transaction data. The model is tested using data from a multi-regional global input-output database and shows remarkable capacity to discover true interregional trade patterns from highly distorted initial estimates.

### **JEL Classification Numbers** : R1, C67, C81

## World Bank Policy Research Working Paper 3359, July 2004

_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._

* Patrick Canning is a senior economist at the Economic Research Services, United State Department of Agriculture, 1800 M street, NW, Washington, D.C. 20036; email: <u>pcanning@ers.usda.gov. Zhi Wang is a consultant at the World Bank and adjunct Professor at</u> City University of Hong Kong. Corresponding address: 838 Summer Walk Drive, Gaithersburg, Maryland 20878. E-mail: zwang53@comcast.net. The authors thank the editor of this Journal and three anonymous referees for their valuable comments.

1
ferences in the remainder of the analysis of the data on developing countries. We further see from this table that the estimates of the _AR_ (1) coefficient obtained with DIF-GMM applied to the series monthly subscription to fixed and price of cellular are smaller than those obtained with SYS-GMM. We conclude that the instruments for the equation in first differences are weak and hence we also use these series in first differences.

Concerning the data on the developed countries, we see from Table A8 that the estimates of the _AR_ (1) coefficient obtained with DIF-GMM applied to the series mainlines per employee ( _eff_ ), monthly subscription to fixed ( _p res_ ), and price of cellular ( _p cel_ ) are also smaller than those obtained when SYS-GMM is applied instead. We therefore conclude again that the instruments for the equation in first differences are weak and use these series in first differences as well.<sup>29</sup>

# **5 Analysis of the relationship between political accountability and regulatory performance**

## **5.1 Causality results**

In this subsection we address the issue of the existence of causal relationships between the variables of political accountability and regulatory performance. Tables A9-A14 given in the appendix show the DIF-GMM estimation results on which we build our testing procedure asking whether the variables of local accountability, namely, the regulatory governance index ( _reg_ ) and global accountability, namely, the institutional environment index ( _institutional_ ) and the index of checks and balances ( _checks_ ), Granger-cause the variables of regulatory performance, namely, mainline penetration ( _ml_ ), cellular subscription ( _cel_ ), mainlines per employee ( _eff_ ), monthly subscription to fixed

> 29In fact, for the purpose of our empirical analysis that seeks to cross-examine the results found with the developing and developed countries data sets, we ultimately use the regulatory performance series in first differences.

17
deficit for the period exceeded the average annual oil revenues by more than 50 percent of non-oil GDP! The resulting large fiscal deficits translated in large current account deficits, which amounted to $18 billion cumulatively over 1981-1983. This in turn led to a rapid build up of external (public) debt.

**Figure 4 a) Public debt decomposition results and b) Trends in Non-oil primary deficit and Oil revenues.**

<!-- Start of picture text --> 40 80<br>30 70<br>20 60<br>10 50<br>0 40<br>-10 1981-83 1984-93 1994-99 2000-05 30<br>-20 20<br>-30 10<br>-40 0<br>NOPD Oil Rev.<br>Seignorage r-n<br>e-hat Oil fiscal savings<br>Other factors Change in public sector debt Non-oil primary deficit Oil Revenue<br>1980 198219841986 1988199019921994 199619982000 20022004<br>Percent of GDP<br>percent of non-oil GDP<br><!-- End of picture text --> During 1984-1993, the public debt to GDP ratio increased substantially and reached a staggering 140 percent of GDP! During this period, public debt increased largely as a result of the large exchange rate depreciation in 1986. Furthermore, the contribution of “other factors” has been particularly large in this sub-period. Other factors would include debt arrears, other hidden/contingent liabilities (a number of guarantees on external state borrowing have been called), and measurement errors.

However, fiscal policy had a debt reducing impact, as the spending came to an abrupt halt when Nigeria effectively was cut off from external capital markets during and after the crisis of 1984. The government responded by a drastic cut in federal and state expenditure, including a priority ranking of the investment program, reduction in public sector employment and reduced subsidies and more broadly, improving cost recovery in the parastatals. This led to halving the non-oil primary deficit compared with its level during the previous period, which actually contributed towards public debt reduction during the period. In addition, seigniorage was used to a substantial degree in the immediate aftermath of the 1984 crisis, but much less so from 1993 onwards.

7