rafmacalaba/data-use-mentions-extended huggingface dataset:
concentration (across producer countries) in the exports of intermediates used by a sector. To obtain (i), we calculate for each HS4 product the share of China in the product’s world exports in 2015. We average this share by ISIC revision 3 broad sector (the classification used in the inputoutput tables), after mapping HS4 products to broad sectors. Then, we use each country’s inputoutput table to construct for each given broad sector X the reliance on China as supplier of its inputs as the weighted average across all the broad sectors’ average China share, where weights are given by the shares of inputs from each broad sector used for production of broad sector X’s output. To obtain (ii), we calculate for each HS4 product the share of its largest exporter in the world in 2015. Then, we use each country’s input-output table to construct for each given broad sector X the export concentration of its inputs as the weighted average across all the broad sectors’ average share of the largest exporter, where weights are given by the shares of inputs from each broad sector used for production of broad sector X’s output. We then map these two measures at the broad sector level into the HS4 level. The resulting measures vary at the exporting country and HS4 product level. Allowing for these two dimensions of variability is important since different countries are likely to source very different inputs.

Fourth, as a proxy for technology, we use product complexity defined as the weighted average of the GDP per capita of the countries that export the HS4 product, where weights are given by countries’ revealed comparative advantage (RCA) index in that product following Hausmann and Hidalgo (2009, 2011). We compute this RCA (Balassa) index, the ratio between the share of an HS4 product in a country’s export portfolio and the share of the same product in world exports, using data from UN COMTRADE and GDP per capita data from the World Development Indicators for 2012
**|-0.0013***|
||(0.0002)|(0.0003)|(0.0008)|(0.0006)|(0.0008)|(0.0004)|
|GFC frm shock*2014*Firm characteristic base 2007|0.0002<br>(0.0002)||||||
|GFC frm shock*2015*Firm characteristic base 2007|0.0002<br>(0.0002)||||||
|GFC frm shock*2016*Firm characteristic base 2007|-0.0002<br>(0.0002)||||||
|Observations|107,541|26,054|26,787|26,178|25,981|26,244|
|R-squared|0.0169|0.0129|0.0144|0.0148|0.0120|0.0139|
|2-digit industry X Year FE|Yes|Yes|Yes|Yes|Yes|Yes|
|State X Year FE|Yes|Yes|Yes|Yes|Yes|Yes|

_Note:_ Robust standard errors clustered at the firm level in parentheses. ***, **, and * indicate significance at 1%, 5%, and 10% levels, respectively. All firm characteristics in base year 2007 enter in logarithms. The specification controls for a vector of firm characteristics as of 2007 described in Section _C._ . L-P refers to Levinsohn & Petrin (2003). ACF refers to Ackerberg et al. (2015). Wooldridge refers to Wooldridge (2009). FE stands for fixed effects.

50
# **Box 2. Financial inclusion in the European Union** : **Insights from the 2017 Global Findex Survey**

- Account ownership varies across EU member states. In Western European countries, such as France, Germany, and the Netherlands, account ownership is virtually universal. Account ownership is lower in some Eastern and Central European economies. The share is roughly 80 percent in the Czech Republic and the Slovak Republic and about 75 percent in Bulgaria and Hungary. In Romania just 58 percent of adults have an account, the lowest share in the European Union.

- Gender gaps are rare in the European Union. In the Czech Republic, Hungary, and Romania, men are roughly 6 percentage points more likely than women to have an account, a gap similar to the average global gender gap.

- Income gaps are evident in some EU countries with relatively low account ownership. Among adults in Bulgaria from the poorest 40 percent of households, 55 percent have an account; for adults in the richest 60 percent of households, the share is 84 percent. In Romania 71 percent of wealthier adults have an account—nearly twice the share among poorer adults.

- Use of digital payments varies widely within the European Union. In Denmark and the Netherlands, virtually all adults make or receive digital payments. The share is about 80 percent in Croatia, Cyprus, and the Czech Republic; about 70 percent in Greece and Hungary; about two‐ thirds in Bulgaria; and about half in Romania. Use of mobile phones and the Internet to make digital financial transactions is highest in Denmark, Finland, and Sweden (80 percent) and lowest in Greece (18 percent) and in Bulgaria and Romania (about 10 percent), among ECA countries with available data.

- With the European Union, the share of adults formally saving is highest in Sweden, at 75 percent. About 60 percent of adults formally save in Denmark, Luxembourg, and the Netherlands. In contrast, only about half of adults in
0.022)|(0.036)|
|Respondent age|-0.001|-0.000|0.000|0.001|
||(0.001)|(0.002)|(0.001)|(0.001)|
|Respondent marital status (single)|0.084|0.120**|-0.032|0.066|
||(0.059)|(0.057)|(0.029)|(0.060)|
|Respondent education level|0.036|0.098***|-0.047***|0.057*|
||(0.031)|(0.030)|(0.016)|(0.029)|
|Observations|6,245|6,332|6,552|6,319|
|R-squared|0.486|0.461|0.236|0.479|

_Source_ : Data for the study comes from a survey of farmers in northern Uganda. The survey was conducted by Innovations for Poverty Action.

Note: This table presents OLS regression results for equation (1). For each column, the outcome variable is (an increasing) categorical variable (1-4) which measures the openness to vote for a political party, namely, the Democratic Party (DP), the Forum for Democratic Change (FDC), the National Resistance Movement (NRM), and the Uganda People’s Congress (UPC). Each regression includes community fixed effects and a constant. For all regression, the sample includes enumerators who have completed at least 24 interviews. Robust standard errors in parenthesis are clustered at the enumerator level. *** p<0.01, ** p<0.05, * p<0.10.

36
of imports, b) weight-to-value ratio, and c) containerized-share of imported shipments. In order to avoid a potential bias generated by endogenous choices of transport mode, we calculate these characteristics in U.S. import data (net of flows from Canada and Mexico). Among final products, we find that PR’s home bias towards imports coming from the U.S. mainland is smaller for products that are vesselshipped, physically heavy, and not typically shipped in containers. Among upstream products, evidence of substitution away from U.S. sources is less apparent; instead the composition of PR’s imports exhibits a strong bias against sea-shipped products in general. These effects are consistent with a hypothesis that the JA has shifted PR’s industrial structure away from sectors that use sea-shipped imports as inputs, though other policies may also have contributed to this outcome.

Since we estimate trade distortions on a single trade route, our empirical methods are somewhat different than conventional approaches to estimating the gravity model of trade. As a robustness check we apply precisely the same methods to the imports of three comparison countries: the Dominican Republic (DOM), Jamaica (JAM) and the Bahamas (BHS). The patterns we uncover in PR do not appear in these other countries; giving credence to the view that the effects we observe for PR are due to the JA, rather than to other anomalies in U.S.-Caribbean trade.

In order to provide quantitative context for our estimates, we incorporate external estimates of product-level elasticities of substitution to infer tariff-equivalent JA trade costs among final products, and conduct a compensating variation (CV) calculation that removes JA tariff-equivalent costs in final demand. Our preferred specification produces a mean JA-tariff-equivalent of 30.6 percent among final products. The CV calculation suggests an annual welfare burden of the policy of $1.4 billion the direction of PR. The container ships that work the route typically return to the mainland with less than full loads and, anecdotally, charge much
# **4 Data and Statistical Outline**

Our investigation covers a total of 153 countries over a 23-years period: 1993-2015.

To measure the cyclicality of fiscal policy, we compute, as aforementioned, the impact of real GDP growth on real expenditure growth using the LGWOLS. Our preference for public expenditure as fiscal policy variable rather than others like primary balance or revenue is motivated by the criticism of Kaminsky et al. (2004). The authors argue that fiscal balance or revenue are results of fiscal policy rather than instruments. In fact, if a government wants to influence economic activity, it would modify its expenditure program or change tax rates and such effects would affect revenue and fiscal balance. Moreover, the advantage of using government expenditures is that co-movements with GDP are able to clearly differentiate between pro-cyclical, a-cyclical and counter-cyclical fiscal policy (Bergman and Hutchison (2015)).

The source of the data on fiscal rules is “IMF Fiscal Rules Dataset 2016” from the Fiscal Affairs Department of the International Monetary Fund. This dataset contains information on all the types of fiscal rules (expenditure rules, debt rules, budget balance rules, revenue rules) and their characteristics for the countries in which they did exist at any time since 1985. We perform our regressions using dummy variables of different types of fiscal rules. FRD stands for fiscal rules dummy, ERD for expenditure rules dummy, DRD is debt rules dummy, BBRD is budget balance rules dummy and RRD is revenue rules dummy.

Our institutional quality variable is “Bureaucracy quality” from International Country Risk Guide (ICRG). Bureaucracy quality represents “the institutional strength and quality of the bureaucracy; a shock absorber that tends to minimize revisions of policy when governments change” (ICRG 2015). It ranges between 0 and 4, with “high points indicating countries where the bureaucracy has the strength and expertise to govern without drastic changes in policy or interruptions in government services. In these low-risk countries, the bureaucracy tends to be somewhat autonomous from political pressure and to
low regulatory burden. On the one hand, we confirm the existence of a positive relationship between digital-tech-oriented firms and both the monitoring of emissions and providing training when the regulatory burden is low, perhaps suggesting that other factors are more effective in pushing the adoption of these standards. On the other hand, we find that a lower regulatory burden increases the gender gap possibly as women are most needed when the regulatory burden is heavy. Again, our findings reflect the dual nature of the relationship between technology firms and the adoption of ethical practices.

Finally, we examine whether the courts are perceived as a relevant barrier to doing business. In this case, we find that digital-tech-oriented firms are negatively associated with hiring a female top manager when the courts are not perceived as a relevant barrier. Similar to the results considering different cultural dimensions, this finding highlights the challenges women face in reaching top management positions when the courts are not perceived as an obstacle to doing business, and there may be greater perceived degrees of freedom in choosing who fills management positions.

This paper presents some limitations that could be addressed in future research. One such limitation is the reliance on cross-sectional data, which restricts the ability to observe changes over time. Incorporating panel data in future studies could enable the analysis of time variation and provide a better understanding of dynamic relationships. Additionally, the study does not fully examine expanded metrics for digitalization, such as digital transaction volumes, effective R&D expenditures, and patent activity. Including these metrics in future research could 21
47 villages from three sites in four districts of Bangladesh<sup>11</sup> . The survey objective was to evaluate the impact of commercial vegetable production in Saturia (site 1), polyculture fish production in household-owned ponds in Mymensingh (site 2), and polyculture fish production in group-managed ponds in Jessore (site 3) on household income, nutrition, and time allocation. In each site, villages were categorized into program villages (A villages) where the technology was already introduced and comparable control villages (B villages) where the technology was yet to be introduced. From each of these categories, surveyed A and B villages were randomly selected. A household census was conducted in all the randomly selected A and B villages, from which households of two categories (adopters and

> 11Bangladesh is divided into six divisions. A division is then divided into districts. A district is composed of several thanas. Thanas are divided into unions. A union is composed of several villages.

14
Policy Research Working Paper 9448

# **Abstract**

The water supply and sanitation sector remains heavily subsidized around the world. Yet, the accounting of water supply and sanitation subsidies globally has proved challenging due to utility-level data limitations and their often implicit nature. This paper develops a methodology to estimate water supply and sanitation subsidies that is adaptable to data scarce environments, while accounting for differences among service providers such as population served (to account for economies of scale), coverage of water and sanitation services individually, and their level of operational efficiency in terms of water losses and staffing. This methodology is based on Chile’s _empresa modelo_ (model firm) approach to cost-reflective tariff estimation and uses utility-level data from the World Bank’s International Benchmarking Network for Water and Sanitation Utilities database. The results suggest that the cost of subsidies associated with the operations, maintenance, and major repair and replacement of existing water supply and sanitation infrastructure in much of the world (excluding, notably, China and India) is an estimated $289 billion to $353 billion per year, or 0.46 to 0.56 percent of the countries’ combined gross domestic product. This figure rises, shockingly, to 1.59 to 1.95 percent if only low- and middle-income economies are considered, an amount largely due to the capital subsidies captured in the estimation. Subsidies of operating costs account for approximately 22 percent of the total subsidy amount in the full sample and for low-income economies separately. Annual subsidy amounts by region range from 0.05 to 2.40 percent of gross domestic product, and low-income economies are generally at the high end of this range. The estimations do not include capital expenditure for infrastructure expansion— which tends to be fully subsidized—or environmental costs. Therefore, the actual global magnitude of networked water supply and sanitation subsidies is much greater than the estimation.

This paper is a product of the Water Global Practice. It is part of a larger effort by the World Bank to provide open
2010 to RMB 37.9 billion in 2015 if the retirement age of female workers is increased gradually from 55 to 60 during that period (Figure 12). The pension fund annual balance increases further from RMB 47.8 billion in 2020 to RMB 133.1 billion in 2025 if the retirement age for all workers is increased gradually from 60 to 65 during that period.

Simulation results also show that increasing the retirement age will promote growth in GDP, investment, and private consumption (Figure 13). The effect on the GINI coefficient, however, is not significant after expanding coverage to rural areas and adjusting the retirement age gradually. This could be attributable to rural-to-urban income transfer in the initial years since the urban population is aging faster than the rural population. This might worsen income distribution since the rural population is much poorer than the urban population. Thus to maintain an equitable income distribution, it may not be advisable to expand pension coverage to rural enterprises too soon.

If a new social security tax is levied, the old fragmented system will become unified across the country, and the reformed pillar 1 will remain financially sustainable, even if the tax rate is lower than specified in State Council Document 26 (Figure 14). Here, raising the retirement age will improve the funding situation further, allowing some accumulation of reserve funds in pillar 1. Simulation results also show that increasing the retirement age will promote growth in GDP, investment, and private consumption (Figure 15).

# **Conclusions**

Ihis paper examines the impacts of various design options for pension system reform on the sustainability of the system and on overall economy growth. We are able to combine the CGE model and population growth model into a recursive dynamic framework, which provides a new flexible tool to simulate various pension reform plans in a general equilibrium setting. We differentiate production and employment by ownership type and organize the demographic data in a matrix with four dimensions. We then conduct three sets of simulations with 18 experiments, (1)
been adopted, with variations and extensions, in several recent World Bank studies on the distributive impact of tax policies, such as (Inchauste & Lustig, 2017) and (Hernández Oré, Sánchez, Sousa, & Tornarolli, 2018).

The study makes use of Mongolia’s Household Socio Economic Survey for year 2016 for this estimation of distributive impact of taxes and transfers. This survey allows for identification of some key fiscal policies with impact upon poverty and inequality: personal income tax (through questions on sources of income earned), value added tax and excise taxes (through pattern of consumption), social security contributions (through sources of income, particularly wages), direct transfers (through questions about reception of pensions and other social assistance transfers), and in-kind transfers (through information about attendance to public school or public health facilities). In addition, the survey also allows measuring the impact of indirect transfers such as subsidized interest rates to mortgage and regulated prices to household electricity and heating (through questions on home ownership and housing debt, as well as energy consumption patterns).

The fiscal policies included in this simulation exercise represent about 50 percent in central government fiscal revenues, and 42 percent of central government expenditures in year 2016. The HSES 2016 data get close to budgetary data in some items such as social benefits (nearly 80 percent of) and personal income tax (100 percent). On the other hand, HSES only captures 38 percent of social security contributions. In the case of VAT and excise taxes on alcohol and tobacco, HSES captures a lower volume than reported in administrative data: 57 percent in the case of the former and only 13 percent in the case of latter (see Table 1).

The tax-benefit incidence simulations are done assuming that Social Security contributions are fully paid by employees, personal income tax by income recipient and VAT/excise taxes by the consumer. No assumptions about tax evasion are adopted. In addition, administrative and capital expenditures are included in the redistribution of in-kind transfers
_next century_ . Proceedings of the Seventh Nile 2002 Conference, Cairo, Egypt, 15-19 March, 1999.

- Folmer, H., P. van Mouche and S. Ragland, “Interconnected Games and International Environmental Problems,” _Resource and Environmental Economics_ , 3: 313-335.

- Gustafsson, J.E. 1989. _Vattenfoervaltning i Frankrike_ . Rapport R21:1989. Stockholm: Byggforskningsraadet.

- Global Water Partnership (GWP), 2000. “Integrated Water Resources Management” Background Paper No. 4, Stockholm: GWP.

- Global Water Partnership (GWP), 2004. “Informal Stakeholder Baseline Survey: Current Status of National Efforts to Move Towards Sustainable Water Management Using an IWRM Approach”  Status Report No. 1, April.  Stockholm: GWP.

- Hinchcliffe, Fiona, John Thompson, and Jules Pretty, eds. 1998. _Fertile Ground: The Impacts of Participatory Watershed Management_ . Stylus Publishers.

- Holling, C.S. 1978. _Adaptive Environmental Assessment and Management_ . New York, NY: John Wiley & Sons

- ICWE 1992. _The Dublin Statement and Report of the Conference_ . International Conference on Water and the Environment, 26-31 January 1992.

- Kemper, K. E. and D. Olson 2000. “Water Pricing: The Dynamics of Institutional Change in Mexico and Ceará, Brazil,” p. 335, Dinar, A. (ed.) _Water Pricing: The  dynamics of institutional change in Mexico and Ceara, Brazil_ , New York: Oxford University Press.

- Kemper, K.E. 1996. _The Cost of Free Water. Water Resources Allocation and Use in the Curu Valley, Ceará, Northeast Brazil_ . Ph.D. Dissertation, Linkoping University, Department of Water and Environmental Studies: Linkoping, Sweden.

- Libecap, G.D. 1994. “The Conditions for Successful Collective Action,” _Journal of Theoretical Politics_ . Volume 6, Number 4, pp. 563-592

- Maddala, G.S. 1989. _Limited-Dependent and Qualitative Variables in Econometrics_
||Control mean|(1)|(2)|(3)|
|---|---|---|---|---|
|**Handwshing facilities**|||||
|HW facilities stocked with water and soap (=1)|0.67|0.057<br>(0.045)|0.071<br>(0.044)|0.062<br>(0.043)|
|Water and soap anywhere in the house (=1)|0.768|0.056<br>(0.034)|0.065**<br>(0.033)|0.067**<br>(0.033)|
||||[8.4%]|[8.7%]|
|**Hand cleanliness**|||||
|Hands Cleanliness Index|7.403|0.205<br>(0.172)|0.226<br>(0.158)|0.21<br>(0.151)|
|**Self-Reported handwashing behaviour**|||||
|HW with soap and water previous to eat|0.402|0.056|0.069|0.095**|
|||(0.050)|(0.049)|(0.044)|
|HW with soap and water before food prep.|0.694|-0.052<br>(0.041)|-0.047<br>(0.040)|-0.042<br>(0.039)|
|HW with soap and water after fecal contact|0.656|-0.0121<br>(0.050)|-0.0000743<br
experience, and some show improvements over time only in the non-project LGAs, not in project LGAs. For example, in 2016, only 29 percent of government officials reported paying property taxes on commercial building they own, which rose to 62 percent in 2018, compared to around 75 percent in both years in the project LGAs.

Fourth, despite our checks of pre-project parallel trends in a key measure of local state capacity—own source revenues, since the project LGAs were not selected at random, there remains a possibility that their trends would have been different in the absence of the program, leading to bias in our difference-in-difference estimates. Nevertheless, the following facts make it difficult to defend an argument that the project had impact that we are unable to discern: that the survey data are exceptionally rich, gathering data on many different aspects of local state capacity, from the experience of both government officials and citizens; that we find no evidence at all of significant improvements in the project areas that are different from improvements in the non-project areas; and that the improvements reported over time in both project and non-project areas are consistent with country-wide changes in Tanzania, regardless of the project. For example, the new President re-centralized the collection of local property taxes. The re-centralization of local property taxes directly affected the project design. While at the outset, one of the main indicators of increasing local state capacity was expected to be increases in local own source revenues, the APA entirely dropped the scoring of this component in its 6th round (2017-2018). Yet, we find increases in local government official reports of local tax efforts, and especially so in non-project areas. Local officials’ payment of their own property taxes increases substantially in non-project areas, and they also are more likely than project-area officials to report efforts to improve local tax collection.

To offer ideas and recommendations from research for further innovation in the design of such projects in Tanzania and beyond, we closely reviewed project documents to understand the general design and theory of change on which