rafmacalaba/datause-encoder-data huggingface dataset:
industry (cement, building stone, tile) in Turkey and Azerbaijan. At the present time, capacity utilization in the industry is extremely low due to low domestic demand and physical barriers to trade: Cement plants are used at below 20 percent of capacity, and stone and tile production stands at about five percent of capacity. If the production capacity were more fully utilized, production could increase by US$40 to 80 million a year. Also, by lowering transport costs, existing exports of low value-to-weight produc':s, such as non-ferrous metal (copper, molybdenum, zinc) ores, concentrates, and synthetic rubber would become more profitable and go up in volume.

# _Supply side_

Outside natural resources and semi-finished products produced on the Soviet-era, plants, the South Caucasus countries have a rather limited export base. Necessary conditions for improved export performance include industrial restructuring and large new investment, especially foreign (which facilitates access to foreign markets and places local producers in international distribution networks). Neither will happen without a major improvement in the business climate. Recent international surveys, including the World Bank/EBRD survey, indicate grave problems in this area. The business climate rankings of the South Caucasus countries are consistently placed at the bottorm of the CIS and transition economies as a whole. Official corruption and red tape are regular occurrences, property rights are poorly protected, and the agency problems abound. A marked improvement in the business climate and in its perception by investors will take a long time, if ever.

Also, the usual problems of the post-Soviet industrial sector have to be addressed, including/especially insufficient working capital, managerial and marketing problems, incomplete restructuring, etc. For instance, Armenia's massive engineering sector has largely lost its markets in the CIS, mostly Russia. Equipment and parts for the defense sector, as well as relatively low-quality industrial and household equipment, composed traditional engineering exports. The markets for most of these products have ceased to exist. It is the problems with the identification of new (that is, old geographically but very much changed) markets and the inflexible product mix that make it very difficult tc, restart exports to the CIS. Therefore, a mere reduction of physical trade barriers is not enough to bring about needed revolutionary changes in export performance.

If progress towards the improvement of the business climate and industrial restructuring remains weak, it is doubtful that the potential of export creation will be fully realized.

Trade in energy and natural resources presents the most obvious export opportunities. It is discussed in detail in Section 4.2. In sum, the Armenian exports to Turkey could increase by as much as US$230 million or more, thanks to the exports of electricity and construction materials. This figure equals total Armenian exports in 1999.

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# **5.2 Offshore firm-level responses**

A possible explanation for the tax reform’s significant negative effects on entry along with the zero effects on economic activity is that the intensive margin accounts for the bulk of the impact on economic activity. To test for this explanation, we move to the analysis at the firm level. As previously discussed, we focus on the balanced panel of incumbent firms that were active throughout the 2009 - 2018 period. This panel comprises the bulk of aggregate economic activity, lending credibility to the hypothesis that this is the key margin of impact. It accounts for between 76% and 97% of overall annual onshore revenues during the period and between 58% and 89% for offshores. Similarly for the overall wage bill, incumbent firms account for 80%-96% for onshores and 66%-84% for offshores.

Our first set of results relates to employment in firms in the offshore sector, measured using social security data. In Figure 6, we present results from estimating equation (3) for a set of outcomes of interest related to employment. In panel (a) we use the log number of employees as the outcome of interest. Since, as documented in section 3, a large share of firms have very few employees, we also present results using other measures of employment level categories - panel (b) uses a dummy for 2 or more employees; panel (c) for 5 or more; and panel (d) for 10 or more.

Throughout our results, we first note that we observe a strong convergence between firms in the offshore and onshore sectors in 2009 - 2010. We attribute that convergence to – the rebound of the Great Financial Crisis (GFC) offshore firms in Tunisia are heavily exposed to the European market and were strongly affected by the economic impacts of the GFC in 2007-2008. So our coefficients for 2009 and 2010 are likely documenting the recovery of those firms in relative terms to the onshore sector. In 2011 and 2012, the two groups of firms show no differential trends. Nor do they show any differential behavior after the reform in 2013 – for most of our employment measures, the coefficients on the offshore sector are small in magnitude and not statistically different from zero. The only exception is the outcome measured as an indicator function for firms with 10 – or more employees but even in that case, the point estimates are positive and suggest 26
growth. We indeed find that youths in the treatment group work in formal sector jobs with hourly wages start about 10%-15% lower than in the control group.

Our study contributes to the literature on active labor market policies (ALMPs). While the overall evidence on the effectiveness of ALMPs in developing countries is mixed (Cr ́epon and Van Den Berg, 2016; McKenzie, 2017), a recent meta-analysis suggests that simple programs that provide clear incentives tend to be most effective (Card et al., 2018). Hence there is a renewed interest in wage subsidy programs. Importantly, most wage subsidy programs target firms rather than workers, with few positive or long-lasting results.<sup>4</sup> Potential reasons for this limited effectiveness include stigma effects of subsidies and firms’ reluctance to file necessary paperwork and comply with other regulations. Who benefits from these programs is also unclear as firms may respond to the wage subsidy by lowering wages.<sup>5</sup> Our intervention addresses these concerns by circumventing employers and paying wage subsidies directly to workers. This approach is commonly used in developed countries to increase labor force participation and supplement wages of low-income workers (e.g. Earned Income Tax Credit in the US) but has, to our knowledge, not been tried in poorer countries, possibly due to implementation challenges of compensating workers directly.<sup>6</sup> In Canada, Card and Hyslop (2005) find that a subsidy for full-time work offered to single parents has short-term positive effects on employment, which fade out after 18 months. Closely related to wage subsidies, employment bonus programs that pay workers for finding and keeping a job failed to increase employment in the Netherlands (Van der Klaauw and Van Ours, 2013). By contrast, programs that subsidize wages for (youth) internships tend to find more positive effects (Gelber et al., 2016; Beam and Quimbo, 2021).

In addition to testing the effect of paying incentives directly to workers, we advance the

> 4Existing studies from the U.S. find either no or limited effects (Burtless, 1985; Dubin and Rivers, 1993; Katz, 1996). More recent evidence from Argentina (Galasso et al., 2004) and South Africa (Levinsohn et al., 2014) finds similarly muted effects. One important exception is Groh et al. (2016) who find that among female college graduates in Jordan, a six-month wage subsidy leads to sizeable employment gains. However, these effects quickly disappear once the incentive expires, suggesting that the marginal productivity of workers is above the minimum wage.

> 5Unless firms increase wages, wage subsidies paid to firms would lower hiring costs. De Mel et al. (2010) find, similar to Groh et al. (2016), that a short-term hiring subsidy offered to firms in Sri Lanka leads to only a temporary increase in employment.

> 6The EITC, which is means-tested and benefits more than 20 million people, has been found to increase labor supply and employment without depressing wages (see e.g. Schanzenbach and Strain (2021)).

5
We denote _y_ ̃ _i_ ( **x** ) the expected income (over all possible employment centers) net of commuting costs for residents of group _i_ living in location **x** , that is: We can calculate _y_ ̃ _i_ using (1) and (2), which gives: From equation (2), we can derive the expected number of residents of income group _i_ choosing to work in _c_ , denoted _Wic_ , providing that we know the number of residents of income group _i_ with their residence in **x** , denoted _Ni_ ( **x** ), in all _x_ . We have: _Housing types._ There are potentially four types of housing, generically denoted _h_ . The four categories include _h_ = _FP_ (“formal private”) for housing formally provided by the private sector, _h_ = _FS_ (“formal subsidized”) for housing delivered under a subsidized-housing program such as the RDP or BNG, and two types of informal housing: _h_ = _IS_ (“informal settlement”) for housing in an informal settlement, and _h_ = _IB_ (“informal backyard”) for housing in a backyard structure of a plot that was initially delivered under a subsidized-housing program.<sup>11</sup> As will be detailed below, subsidized housing is accessed outside a market-determined price (see below) but a market exists for formal private housing ( _h_ = _FP_ ) as well as for informal backyard structures ( _h_ = _IB_ ) and for informal settlement structures ( _h_ = _IS_ ).<sup>12</sup> In line with empirical observations, we assume that the set of housing options varies across income groups, with only the lowest income groups considering the possibility of informal housing. In our framework, individuals from income group 1 (the poorest) are eligible for public housing. Only a fraction of individuals from this income group, however, will benefit from the relatively

> 11Note that no central, authoritative registry of public housing is available in Cape Town documenting all housing delivered under the succession of government programs that were implemented since the 1920s (Wilkinson, 2000). Earlier public housing varies greatly in terms of typology, tenure arrangement and quality, and some of it has subsequently re-entered the formal housing market. For the purpose of this model, a series of explicit neighborhood, zoning, and physical attributes were used to delineate public housing characteristic of the RDP and BNG housing programs from overall housing stock in existence today.

> 12Although local surveys suggest that a significant proportion of beneficiaries resell the properties that were initially allocated to them under subsidized-housing programs (Tissington et al., 2013), for simplicity, we do not model this secondary market. Because the sales likely remain within the same income group, this has no impact on income sorting in the model.

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9 Kilpatrick (t973) concludes, on the basis of surveys, that the elasticity of the poverty line with respect to income Is about 0.6. Similarly, Smith and Welch (1989, p.524) assume an elasticity of 0.5. Using surveys, Hagenaars and van Praag (1982, pp. 151-2) obtain an elasticity of 0.54 If Income distribution does not charnge (elasticity is greater with a more unequal distribution). Finally, for Yugoslav republic of Slovenht Stanovnik (1989) estimates, on the basis of surveys, Income elasticity of poverty line for urban households at 0.57.

If we plot a variable _poverty line per capita/average wage_ against an indicator of the level of development (real per capita consumption at International prices) for both market and socialist economies we observe (see Figure 1) that among the latter on!y Hungary stands out with a poverty line which seems too high for its level of Income. Poland and Yugoslavia are almost exactly on the regression line. The elastic ty of the poverty line with respect to income (or wage; here treated interchangeably) Is about 0.56, which Is consistent with earlier findings.9 The second argument often mentioned to explain relatively high level of poverty lines In socialist economies (which, as we just saw, can apply only to Hungary) Is that poverty lines In socialist countries represent simply accounting devices which are devoid of any policy role. Households below the poverty line are not entitled to any benefits. Consequently, "statistical" poverty lines can be set at relatively generous levels. There may be some merit In this view as poverty lines which do carry policy Implications (e.g. West German line denoted Dl In Figure 1, and UK poverty line) are rather on the low side. German example Is particularly partinent since an estimated poverty line not related to policy is 2.5 times higher than the official line which triggers access to welfare benefits. It is quite likely that, to the extent that Poland, Hungary and Yugoslavia move closer to market economies and a welfare system appears, official poverty lines will be lowered, if for nothing else then because it would be financially Impossible to give Income support to say, one-fourth of the population.
institutions have been generally slow, lagging behind the development of security forces like the ANA. This imbalance, as well as the lack of progress in some security subsectors (e.g. justice), carries serious risks. It is essential to develop good governance and sound and sustainable financial management practices throughout the security sector, in line with and integrated with national budget processes and fiduciary provisions.

# **6.2. Toward a Fiscally Sustainable Security Sector**

Decisions on and investments in force levels, salaries, non-salary staff-related costs, standards of equipment, base construction, etc. in the security sector are leading to a fiscally unsustainable situation—for the security sector itself and for Afghanistan’s budget as a whole. Figure 7 below illustrates the dilemma that for some years to come, planned/forecast levels of security sector expenditures will exceed likely domestic revenues, under a somewhat ambitious yet reasonable “base case” of revenue mobilization and even more under a “low case”. These expenditure forecasts are conservative and based on earlier targeted ANA and ANP sizes, and do not include any provision for further rises in wages or increases in other costs. And in any case, allocating the bulk of domestic revenues to the security sector is not viable or desirable over the medium term.

**Figure 7: Forecast Security Sector Spending Against Projected Revenues (US$ million)**

<!-- Start of picture text --> 1,800<br>1,600<br>1,400<br>1,200<br>1,000<br>800<br>600<br>400<br>200<br>-<br>2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10 2010/11 2011/12 2012/1<br>Security - total budget Security - total core budget Security - recurrent<br>Revenues - Base Case Revenues - Low Case<br>Source: World Bank (2005b, Volume V, Chapter 4).<br><!-- End of picture text --> This situation, which stems from the large (albeit of uncertain duration) availability of external resources outside the Government Core Budget (i.e. in the External Budget), fragmented decision-making and lack of cost-consciousness, difficulties faced by the Government in exercising strategic coordination of security sector spending, and limitations on oversight by entities like the Ministry of Finance, urgently needs to be addressed. A recommended set of near-term actions includes the following:

- **Greatly enhance the information base on security sector expenditures,** especially the cost implications of planned expansion of security forces, and also of associated wage structures and non-wage recurrent expenditure requirements.

- **Review the fiscal implications of ongoing security sector expansion and reforms.** The Government should conduct an integrated security sector-wide fiscal review to forecast the fiscal implications of currently programmed security sector

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Wu, Jie; Fan, Ying; Xia, Yan (2016). The Economic Effects of Initial Quota Allocations on Carbon Emissions Trading in China, Energy Journal, Special Issue 1, Vol 16, pp. 12951.

- Wu, Libo, Haoqi Qian and Jin Li (2014). Advancing the Experiment to Reality: Perspectives on Shanghai Pilot Carbon Emissions Trading Scheme. Energy Policy, Vol. 75, pp. 2230.

Yuan, Y.N., M.J. Shi, N. Li, and S.L. Zhou. (2012). Intensity Allocation Criteria of Carbon Emissions Permits and Regional Economic Development in China—Based on a 30Province/Autonomous Region Computable General Equilibrium Model. Advances in Climate Change Research 3(3): 154–62.

- Zhang, D., M. Springmann and V.J. Karplus (2016). Equity and emissions trading in China. Climatic Change, 134: 131–146.

Zhang, Da; Valerie J. Karplus, Cyril Cassisa and Xiliang Zhang (2014). Emissions Trading in China: Progress and Prospects. Energy Policy, Vol. 75, pp. 9-16.

Zhang, Hao (2013). Design Elements of Emissions Trading Regulation in China’s Pilot Programs: Regulatory Challenges and Prospects. Environmental and Planning Law Journal 30 (4): 342–356.

Zhang, Junjie, Zhenxuan Wang, and Xinming Du (2017). Lessons Learned from China’s Regional Carbon Market Pilots. Economics of Energy & Environmental Policy 6 (2): 19–38.

Zhang, Z. X. (2015). Carbon Emissions Trading in China: The Evolution from Pilots to a Nationwide Scheme, CCEP Working Paper 1503, April 2015. School of Economics, Fudan University, Shanghai, China.

Zhu, Lei; Zhang, Xiao-Bing; Li, Yuan; Wang, Xu and Guo, Jianxin (2017). Can an Emission Trading Scheme Promote the Withdrawal of Outdated Capacity in Energy-Intensive Sectors? A Case Study on China's Iron and Steel Industry. Energy Economics, v. 63, pp. 332-47.

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40 re-employed; in Great Britaln, for example, only 60 percent of women age 50.59 receMng unemployment benefits actually sought jobs (Laczko and Phillipson 1991; OECD 1990).

Before taking this as evidence that the programs succeeded, one must ask whether older workers such as these might have reentered the labor force without the early-out benefits, and what the economic consequences of offering the benefits were. Surprisingly litle research has explored this question. Layard and others (1991: 566) compare unemployment trends and the growth of early retirement across many developed nations, and conclude that 'he countries that have experienced more early retirement (often encouraged by govemment policy) are those with the biggest rise in unemployment." The direction of the causal relationship was not explored in that study. Certainly this question should be a high priority research topic for policymakers in the retirement arena.

One topic that no one has devoted much attention to is the question of whether continued work might have been an option for many early retirees, since they were quite young (many in their 50s) and probably in no worse health than previous generations which worked far longer. Had this cohort remained In the labor force, it might have exerted downward pressure on wages by swelling the ranks of those seeking jobs. To the extent that wage rigidity has been identified as a major cause of unemployment, it is at least possible that early retirement schemes could have actually raised rather than lowered overall joblessness, by permitting high end rigid wages to remain in effect longer. Indeed in West Germany, older women's and men's unemployment rates were three to five times higher in 1989, as compared to 1977.36 What they would have been without the programs is uncertain.

A related question Is whether younaer workers' labor market options would have been markedly worse, had the early retirement options not been in effect. More evidence on this point is needed, but there Is reason for skepticism. An early-out policy which reduces the supply of older workers can Improve demand for younger workers only when the two age groups are substitutes in production, and this has not been demonstrated. A study of substitution between different age groups of workers using data from the United States concluded that 1) within a given gender group, workers from different age groups are complementary (with the exception of teenagers); and 2) most substitution occurs across
# 3.8. Data for the approximation of economic impacts

This section describes non-spatial aggregate statistics used to convert exposure shares into economic figures in the sectors tourism, aquaculture, and agriculture.

To approximate the economic impact of hazards on the tourism sector, macroeconomic estimates were sourced from World Bank open data<sup>4</sup> and publications. National tourism GDP was obtained by applying the contribution of tourism to GDP in 2017 (WTTC, 2018) to the national GDP in 2017 (World Bank, 2019). The number of direct jobs in the tourism industry in 2017 are obtained from numbers published by the World Travel and Tourism Council (WTTC, 2018).

In the fisheries sector, aquaculture output in tons per province in 2017 was sourced from the General Statistics Office of Vietnam (GSO, 2019). Total country export value of aquaculture production for 2017 (Danh, 2016; VietNam News, 2019) has been estimated after applying a 65 percent contribution of aquaculture to the total fisheries sector 2020 (Dinh, 2017a). The number of jobs in the aquaculture sector is estimated using the number of jobs created per ton of output from the National Fisheries Development Strategy to 2020 (Dinh, 2017a). Assuming no significant change in productivity from the 2020 outlook in 2017, this number has been used to estimate the amount of jobs in the aquaculture sector using actual production for 2017.

Vietnam’s combined agriculture, forestry and fishing GDP for 2017 and the combined employment in agriculture (that is, from agriculture, forestry and fishery) for 2017 has been sourced from World Bank macroeconomic indicators (World Bank, n.d.). To estimate the contribution of the cultivated crops sector to the combined agriculture-forestry-fisheries sector, contributions of these individual sectors to the combined agriculture sector have been sourced from different World Bank publications (Dinh, 2017a, 2017b, 2017c; World Bank, 2010). For aggregated cultivated crops the provincial area used for cultivation is derived from the researchers’ own calculations, retrospectively aligned with national estimates for 2017 from the General Statistics Office of Vietnam (General Statistics Office of Vietnam, n.d.). For rice, provincial production area and provincial yields for 2017 have both been sourced from the General Statistics Office of Vietnam(General Statistics Office of Vietnam, n.d.). Export values for rice for 2014 and the contribution of rice to the aggregated export value of cultivated crops for 2014 have been derived from World Bank publications (Dinh, 2017b). From this, the aggregated export value of cultivated crops for the same year has been estimated. Employment in the rice sector has been estimated using a labor intensity of rice production of 0.6 workers per hectare (Nolte and Ostermeier, 2017).

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