rafmacalaba/datause-encoder-data huggingface dataset:
## **Table 11. Potential Growth Effects of Improving PM 2.5 Levels for African Firm**

Here, we only report those “policy instruments” with the following characteristics. First, the instrument must be statistically significant for the specific growth result for the African countries. Second, the instrument must be something that the government might be able to do something.

||**African coeff.**|**Improve by one**<br>**Africa-SD**|**% African SD in the outcome**<br>**explained by one Africa-SD**<br>**improvement in the instrument**<br>βaaa∗σX,aaa<br>σY,aaa|
|---|---|---|---|
|**For L-Growth**:<br> <br>||||
|σY,aaa= 0. 14<br> <br>||||
|<br>PM 2.5(at x=mean)<br>|0.0032|8.064|14.89%|
|<br> <br>PM 2.5(at x=40)<br>|-0.0199|-8.064|92.99%|
|<br> <br>**For LP-Growth:**<br> <br>||||
|σY,aaa= 0. 51<br> <br>||||
|<br>PM 2.5(at x=mean)<br>|0.0041|8.064|5.48%|
|<br> <br>PM 2.5(at x=40)<br>|-0.0479<br>|-8.064<br>|64.78%<br>|
|<br> <br>Note. The coefficients are for<br>different values for x, with th<br>coefficient forPM 2.5<sup>2</sup>, andδ|the African regions.<br>e following equation:<br>3the coefficient for|That is, they are based on Tab<br> δ1+ 2δ2x+ 3δ3x<sup>2</sup>, whereδ<br>PM 2.5<sup>3</sup>.|le 9. They have been calculated at two<br>1is the coefficient forPM 2.5,δ2the|
|<br>This table reports the associa<br>changes by one standard devi|<br>ted change (in percen<br>ation (in Africa).|<br> <br>t of one standard deviation o|<br>f the outcome in Africa) when pollution|

The impact is even more shocking when looking at pollution levels (Table 11). After relatively low PM 2.5 concentration levels, the effects turn negative, with a huge impact on both, employment growth and labor productivity growth. For example, at 40 μ , a reduction in one standard deviation of PM 2.5, approximately 8 units, is associated with an increase in /mm<sup>3</sup> employment growth in 93% of its standard deviation (0.172), for African firms. This huge effect translates in an increase of 16.03% in employment growth rate. At the mean level, the annual employment growth rate in Africa will go from 4.1% to 20.1%. For labor productivity, the same exercise yields an increase in labor productivity growth of 38.63 percentage points, which at the mean translates in a positive growth rate of 32.8%.

# 6. Conclusions

In this paper, we shed some light on how air pollution and business environment affect city competitiveness through firm performance, particularly for African firms. We measure firm performance with two variables, employment growth and labor productivity growth. We use 23
reduced modestly over time. The change in budget deficit will release funds financing the investments as illustrated above.

**Table 4: Government Accounts**

|||**Base**|**Reform**|**Reform,**<br>**Prices**|**Reform,**<br>**Prices &**<br>**Phase out**|
|---|---|---|---|---|---|
|**Billion E£**|2013/14|2024/25|2024/25|2024/25|2024/25|
||||% GDP|||
|**Revenue**|25.7%|24.9%|24.5%|21.1%|20.0%|
|**Energy Subsidies**|9.2%|10.3%|8.5%|4.1%|-0.6%|
|**Transfers to households**|10.9%|7.3%|7.0%|6.5%|6.0%|
|**Other Current**<br>**Expenditure**|13.8%|12.8%|12.8%|13.1%|12.9%|
|**Government Deficit**|-8.2%|-5.4%|-3.8%|-2.6%|1.8%|

_Source:_ Authors estimates

# **Balance of Payments**

Reforming energy subsidies will have several effects on external balances: Imports and exports would both increase over time, although as noted, exports are expected to increase slightly more rapidly. This leads to a gradual fall in the trade deficit (Table 5). The capital account surplus will also decline in line with the trade deficit.

**Table 5: Balance of Payments**

|||**Base**|**Reform**|**Reform,**<br>**Prices**|**Reform,**<br>**Prices &**<br>**Phase out**|
|---|---|---|---|---|---|
||2013/14|2024/25|2024/25|2024/25|2024/25|
||||% GDP|||
|**Current Account Balance**|-0.6%|-0.7%|-0.6%|-0.5%|-0.5%|
|**Trade Balance**|-1.8%|-1.5%|-1.5%|-1.4%|-1.3%|
|**Transfers and remittances,**<br>**net.**|1.2%|0.9%|0.8%|0.8%|0.8%|

_Source:_ Authors estimates 15
<!-- Start of picture text --> Appendix B: Components of Aggregate Governance Indicators, 2005<br> Table B1: Voice and Accountability<br>Code Table Concept Measured<br>Representative Sources<br>EIU A9 Orderly transfers<br>Vested interests<br>Accountability of Public Officials<br>Human Rights<br>Freedom of association<br>FRH A11 Civil liberties : Freedom of speech, of assembly and demonstration, of religion, equal opportunity, of excessive governmental<br>intervention<br>Political Rights : free and fair elections, representative legislative, free vote, political parties, no dominant group, respect for<br>minorities<br>Freedom of the Press<br>GCS A28 Newspapers can publish stories of their choosing without fear of censorship or retaliation<br>When deciding upon policies and contracts, Government officials favor well-connected firms<br>Effectiveness of national Parliament/Congress as a law making and oversight institution<br>HUM A26 Travel: domestic and foreign travel restrictions<br>Freedom of political participation<br>Imprisonments: Are there any imprisoned people because of their ethnicity, race, or their political, religious beliefs?<br>Government censorship<br>PRS A23 Military in Politics The military are not elected by anyone, so their participation in government, either direct or indirect,<br>reduces accountability and therefore represents a risk. The threat of military intervention might lead as well to an anticipated<br>potentially inefficient change in policy or even in government.<br>Democratic Accountability. Quantifies how responsive government is to its people, on the basis that the less response there<br>is the more likely is that the government will fall, peacefully or violently. It includes not only if free and fair elections are in<br>place, but also how likely is the government to remain in power.<br>RSF A24 Press Freedom Index<br>WMO A15 Institutional permanence: An assessment of how mature and well-established the political system is.<br>Representativeness :How well the population and organized interests can make their voices heard in the political system<br>Non-representative Sources<br>AFR A2 Elections are free and fair<br>BTI A4 Stateness<br>Political Participation<br>Institutional Stability<br>Political and Social Integration<br>CCR A11 Civil Liberties<br>Accountability and public voice<br>FHT A11 Political Process: Deals with elections, referenda, party configuration, conditions for political competition, and popular<br>participation in elections.<br>Civil Society : Highlights the degree to which volunteerism, trade unionism, and professional associations exist, and whether<br>civic organizations are influential<br>Independent Media: Press freedom, public access to a variety of information sources, and the independence of those<br>sources from undue government or other influences.<br>GAL A12 Fairness of elections<br>Satisfaction with democracy<br>LOB A20 Satisfaction with democracy<br>Trust in Parliament<br>MSI A19 Media Sustainability Index<br>WCY A18 Transparency of Government policy<br><!-- End of picture text --> 82
private transfers, private pensions income and the value of imputed rent.<sup>17</sup> Under the CEQ approach, there are two options for treating pensions. Here we treat Pensions as Deferred Income (PDI), which uses _market income plus pensions_<sup>18</sup> (hereafter simply referred to as ‘ _market income_ ’) as the starting point of the assessment. This treats contributions to pensions made during working-years as mandatory savings that would be enjoyed later in life; during retirement the income from contributory pensions are considered part of the pre-fiscal income. An alternative is to treat the income from pensions as a government transfer (PGT) and the contributions as direct taxes.<sup>19</sup> The movement from one income concept to the next is done by iteratively assigning taxes and transfers as seen in Figure 1 until reaching ‘final’, or ‘post-fiscal income’. ‘Disposable income’ is that resulting from adding direct government cash and near-cash transfers and subtracting direct taxes and contributions to market income. ‘Consumable income’ then subtracts indirect taxes and adds indirect subsidies. ‘Final Income’ adds the public cost of providing in-kind transfers (services which are not received as cash benefits, namely health and education).

HEIS contains information on household income and consumption and the official poverty measurement uses consumption as the welfare aggregate. Following standard methodology (Lustig 2018), this means that in practical terms the calculation of the income concepts begins by equating household consumption to disposable income and then working backward (subtract direct transfers and add direct taxes) to construct market income.

To assess the impact of the fiscal instruments on poverty we use the national poverty line. Impacts across deciles of the consumption distribution and the Gini coefficient are used to capture the distributional impacts. We model the following fiscal instruments: Personal income tax (PIT), benefits from NAF, the bread subsidy compensation scheme and other cash transfers, sales taxes (GST and SST), water and electricity subsidies, and health and education in-kind benefits. The allocation of the fiscal instruments to households is done primarily based on the reported information in the household survey, making some adjustments to reconcile administrative figures when necessary. This means that the analysis already incorporates inclusion and exclusion errors in the allocation of different interventions.

> 17 A house owned by the household can be rented out or resided in. To compare across households making different decisions, the foregone rent for those who live in houses they own is estimated and added to household income.

> 18 Where income from pensions is added to factor income and contributions to old-age contributory pensions are subtracted from factor income.

> 19 Pension status is not recorded in HEIS. Instead, we use the self-reported income and expenditure information in HEIS to determine the amount of pension income received, and the contributions made to the pension system. We show the results from this sensitivity assessment in Appendix 2.
While none of the above constitutes an ideal measure of the evolution of costs of schooling—the former because of the different dynamics of population growth and enrollment, and the latter because the lack of data on tertiary enrollment—they suggest an increase in spending on education when accounting for enrollment.

# **3. Expansion of Schooling: A Deeper Look**

Comparing figures across time reveals an interesting fact: controlling for income, the pace of educational enrollment has increased quite significantly. In other words, a currently advanced country at an earlier phase of its development had much lower educational enrollment than its modern developing counterpart. This can be seen from figure 4 below, which shows that, with time, income “buys” more educational attainment.

**Figure 4: Educational Expansion over Time**

<!-- Start of picture text --> 5 6 7 8 9 10<br>Log real GDP per capita<br>1965 1980 1995<br>2<br>1<br>0<br>Fitted Log Years of Schooling<br>-1<br><!-- End of picture text --> This finding can be interpreted in at least two ways. Either the productivity of school spending has increased, decreasing the marginal cost of enrollment; or the demand for schooling has grown over time; or a combination of the two.

Existing evidence, however, suggests that the productivity of education spending has not increased. Thus, Gundlach and others (2001), find that, in a sample of OECD countries between 1970 and 1994 it actually decreased, for many countries quite substantially and even more so than the “productivity collapse” in the U.S. schools diagnosed in Hanushek (1997). They interpret this finding as being in line with the Baumol’s (1967) cost-disease model, which indicates a relative cost increase in the service sector.

To confirm this in our sample, we ran a regression of the average years of schooling on public spending for different years, both in logarithms; the regression coefficient is thus interpreted as the elasticity of years of schooling with respect to spending. The elasticity has been steadily decreasing over time, from .24 in 1965, to .19 in 1975, to .14 in 1990. Furthermore, research done by Hanushek strongly indicates that the quality of a year at school has not improved (see, e.g., Hanushek 1997), suggesting that spending productivity has decreased over time. Thus, the reason for a massive 7
Policy Research Working Paper 10601

# **Abstract**

Quality regulations imposing minimum product standards have become a central instrument of trade policy. Using disaggregated panel data from middle-income countries, the authors show that sanitary and phytosanitary (SPS) and technical barriers to trade (TBT) measures increase trade on average, consistent with improved consumer information and contrary to their depiction as “non-tariff barriers”.

However, their distributional effects differ. SPS measures reallocate trade toward higher-income countries, whereas TBT measures favor lower-income countries. Both increase sales concentration among exporters from lower-income countries only. The evidence indicates that the costs of quality regulation are primarily borne by exporting firms, especially those from lower-income countries.

This paper is a product of the Development Impact Group, the Development Impact Group, Development Economics and the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at lzavala@worldbank.org, afernandes@worldbank.org, treed@worldbank.org, reyes@worldbank.org, and ryan.haygood@yale.edu.

_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 views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
An overall summary of the transactions data is as follows: Total turnover (nominal value) of futures and options derivatives quoted on organized exchanges came to USD 2214 trillion in 2008. (About two-thirds were interest rate futures and rather more than a quarter were interest rate options). Estimated turnover in OTC exchange rate and interest rate derivatives came to USD 1250 trillion, of which two-thirds related to exchange rate contracts and the remainder to interest rate contracts.<sup>22</sup> Thus in broad terms, the total turnover of derivatives is of the same order of magnitude as payments transactions, if slightly smaller. Unfortunately, we have no full breakdown of how many of these transactions relate to non-financial firms.

Extending the scope of a general transactions tax from payments transactions to transactions involving derivatives and applied to the total nominal value of the objects of those derivatives about doubles the initial base of the tax.

As discussed in the next section, the elasticity of the base of tax on derivatives to the tax rate may, however, be much higher.

# **5.  Impact on behavior and on the base**

The base of a transactions tax is likely to be very elastic in response to a tax. The top of the Laffer curve might be reached at a surprisingly low level.

Mende and Menkhoff (2003) have argued rather convincingly that even a very small tax would dramatically alter the way in which wholesale participants in the foreign exchange market operate. Drawing on a specialized literature which studies the microstructure of the foreign exchange market (cf. Lyons, 2001), they point out that the strategy of the typical bank participant involves buying and selling foreign exchange as if it was a hot potato. Their goal in this is to minimize the risk that they are uninformed about a change in prospects. For that reason they will not want to accumulate a significant stock. They

> 22 In contrast, the stock of OTC exchange rate related derivatives is only one-eighth that of interest rate derivatives.  The exchange rate derivatives have a much higher ratio of turnover to end-period stock, probably reflecting in part their very short median maturity and the microstructure of this market discussed above.

20
Figure 5.1: Calibration of Distortions and Reforms <!-- Start of picture text --> 0.6 0.6<br>G<br>G GGG<br>G<br>GG<br>0.4 0.4 G<br>0.2 0.2<br>G Estimated Value<br>G Linear Fit<br>0.0 0.0<br>2000 2005 2010 2015 2020 2000 2005 2010 2015 2020<br>Year Year<br>Profit Tax<br>TFPR−TFPQ elasticity<br><!-- End of picture text --> NOTE: The left panel illustrates the regression coecient between _log_ ( _TFPR_ ) and _log_ ( _TFPQ_ ) for the period 1998-2011. The dots correspond to the point estimates from China's Annual Survey of Industrial Production for 1998 through 2005. We dene _log_ ( _TFPR_ ) and _log_ ( _TFPQ_ ) as in Hsieh and Klenow 2009. The solid line illustrates a linear t on the estimated values projected on to 2011. We assume that reforms stabilize in 2011, and the productivity-elasticity of idiosyncratic distortions remain constant a the 2011 level. The initial steady state is represented by the elasticity estimate for 1998. The right panel illustrates the calibration of the prot tax. The solid dot corresponds to our calibration for 1998, while the solid line corresponds to the reform. The initial value is calibrated, jointly with the xed production cost, targeting the earnings share of the richest top 1% of households and the average rm size. The solid line is calibrated to replicate the average rm size dynamics during the transition.

investment rate, and the innovation expenditure rate for each reform.

Figure 5.2 shows that the model can capture the qualitative features of growth accelerations in the data. In particular, the model delivers a protracted path for measured _TFP_ and a hump-shaped behavior of the investment rate. In reforms lifting idiosyncratic distortions, the main driver of these two features is the innovation decisions of rms. Absent any reallocation friction, the allocative eciency gains accrue immediately. Moreover, the removal of distortions encourages the most productive rms to innovate, accelerating the convergence. However, the enhanced incentives to innovate by the most productive rms coexist with the disincentive to innovate among the least productive ones, who beneted from the distorted environment. Given the stochastic nature of entrepreneurial ability, it takes time for these rms to exit the market, a force that protracts the transition. When lifting entry distortions, on the other hand, the most relevant force protracting the transition is given by the dierence in the distribution of entrepreneurial talent between entering rms and in27
account for a significant portion of the country’s trade. Thus, the instrument reflects the tradeweighted average of the economic growth of the most relevant trading partners, effectively capturing external demand. The key assumption is that the growth of trading partners primarily influences the GDP growth of country i, with limited or no direct effect on domestic public spending decisions through other channels.

Drawing from Auerbach and Gorodnichenko (2011), our proxy function for the economic cycle is defined as: Here, is a normalized variable that measures the state of the business cycle. It is calculated using a 3-year moving average of the growth rate of real output and then normalized so that ii,ii zz ) = 0 and V ) = 1 for each country i. Finally, is a set of controls including the lag of total public expenditure and the lag the dependent variable. ii ii ii,ii−1 EE(zz rr(zz VV The second stage follows: Where is a vector of the real growth rate of public spending components for country i and time t, represents the estimated growth rate of real output in the first stage. Here ii,ii 1I and 2I GG represent the causal effect of income to public spending during expansions and recessions ii,ii YY<sup>�</sup> ββ ββ respectively.

To uncover differences across different country groups, we split the sample between advanced and emerging economies.
**Stylized Fact 15.** _The ranking of freight rates depends on their measure. In ad-valorem terms, the drybulk freight rate is up to 5 times_ greater _than the containerized (non-refrigerated) freight rate. However, the specific (per kilo) dry-bulk freight rate is up to 10 times_ lower _than the containerized one._

**Stylized Fact 16.** _The freight rate trends of the containerized and dry-bulk freight rates are not synchronized, implying that the cost and demand shocks are either asynchronous or have asymmetric effects on transport costs across commodity types._

**Stylized Fact 17.** _The aggregate per-kilo and per-TEU trends for a given commodity type are synchronized._

The last fact is important from a practical standpoint since per-kilo freight rate measures are available in many more datasets. These similarities in trends indicate that, in the absence of the per-TEU measures, the per-kilo trends are good proxies for the per-TEU trends.

Finally, some datasets provide the per-container charges. In some cases, these datasets contain the spot-market, but not the annual-contract charges (e.g., Drewry, as described by Wong, 2020). The US Bills of Lading data provide per-container charges, but only for a limited sample of the shipments.<sup>23</sup> These data limitations impede utilizing the per-container freight rates in the context of international trade.

# **4 Containerized Maritime Shipping: Freight Rate Determinants**

Containerized maritime shipping is a multi-billion industry with complex and sophisticated technology. While an exact functional form of transportation cost is difficult to derive, it includes both fixed and variable cost components. The variable cost depends on the market structure, network organization, distance and geography, volume of trade and directional imbalances, good- and variety-specific imbalance: e.g., empty reefer boxes are needed for the Chilean exports, and therefore the empty returns to Chile are very cheap.

> 23These data have been used by Holmes and Singer (2018) and Terner (2021). The value of the transported goods is also often missing from the data.

26