rafmacalaba/datause-encoder-data huggingface dataset:
equals one if both countries share a border is included. Bilateral trade can also be fostered by countries’ cultural proximity. This proximity is controlled for by introducing two dummies that are equal to one if both partners share an official language (clang _ij_ ) or if they have had a colonial relationship or a common colonizer (colony _ij_ ), respectively. The data come from the above-mentioned CEPII database.

The last step is to specify the variables used to quantify the effect on South-South and North-South trade of incorporating provisions on standards harmonization in a North-South EIA. The full list of North-South EIAs considered in our exercise is provided in Appendix (Table A.2) and covers 43 EIAs. We use the template provided by Piermartini and Budetta (2009) and update it by adding some recent North-South EIAs that they did not review. For each EIA, our focus is on provisions on technical regulations. According to the WTO definition, compliance with a technical regulation is mandatory. To build their template, Piermartini and Budetta (2009) focus on the legal text of the Agreements<sup>6</sup> and scrutinize the wording. Expressions inviting parties to “bridge the gap,” “reduce divergence,” or “make compatible” their standards and technical regulations indicate that the policy adopted is harmonization.

Before turning to estimation results, we briefly report descriptive statistics showing the expansion of North-South EIAs over the 1990–2006 period. These statistics provide the number of North-South EIAs and the share of Northern imports from the South covered by these EIAs in 1990, 1999, and 2006 (Table 1). The number of EIAs expanded from four in

> 6 ~ The database on EIAs maintained by Baier and Bergstrand (http://www.nd.edu/ <u>jbergstr/) also provides</u> detailed and useful information on EIAs and links to the legal text of the Agreements. Similarly, Horn et al. (2009) study the legal text to investigate whether the areas (technical regulations as well as customs administration, export taxes, public procurement, and labour market regulations) covered by the Agreements fall under or outside the current mandate of the WTO. We thank A. Sapir for providing data. We tried a cross-check with our data. Unfortunately, their database does not provide a detailed analysis of the content of each area.

20
protected, pirates are more likely to switch to less-protected smaller ships. The convexity of the iso-crime curves hints that it is hard to eliminate the piracy problem using a single policy measure, and that a cost-effective policy would consist of a combination of both public and private protection instruments.

To estimate the cost-effective combination of policy interventions to reduce the number of attacks, we first estimate the costs of private and public security provision. The cost estimates of private maritime security contractors are available in the literature. While studies such as Besley, Fetzer and Mueller (2015) or World Bank (2013) give aggregate costs associated with Somali piracy, they do not provide a breakdown of these costs. The methods used are based on increased private costs borne by shipping companies and are also likely to ignore the contributions of taxpayers of each country involved in the naval coalitions. The One Earth Future Foundation, a not-for-profit organization, first provided the estimates of private maritime security in their Oceans Beyond Piracy (OBP) 2012 report, and they set the cost of private maritime security contractors at US$50,000 per trip through the troubled waters (Oceans Beyond Piracy 2013). In the later years, they provided more detailed estimates: at around US$33,250 per trip in 2013 (Oceans Beyond Piracy 2014), and US$22,975 per trip in 2014 (Oceans Beyond Piracy 2015). For our exercise, we use the year-specific estimates of costs after 2011, and the rough estimate of US$50,000 per trip for earlier years. To map the per trip cost to an increase in _k_<sup>_t_</sup> , we also need information on the traffic volume through the troubled waters. We again turn to the traffic statistics from the Suez canal for a traffic estimate in each year, and compute the costs of a one percentage point increase of protected vessels per year. As the Suez canal traffic underestimates overall traffic through the troubled waters off Somalia, our estimates of private team costs tend to be underestimations as well. For this reason, we carry out a set of robustness checks with doubled costs of armed protection. The results presented in Figure 16 are essentially the same as in our benchmark case.

The estimated costs of navy patrols also come from various OBP reports. In 2010, OBP provided a first estimate of around US$30.2 million per patrol – including the costs of personnel, fuel, and other administrative supports (Oceans Beyond Piracy 2013). This estimate is almost surely an upper bound, as it assumes that the warship patrols year-around.

40
8

- Alternatively, the _collusive market_ theory predicts that when current demand is high relative to future demand, the incentive for any firm to cut its price rises because it becomes more valuable to capture current sales than to maintain collusion in the future. The inflation rates should now decrease (c3 < 0) in the short-nin with current excess demand but increase in the longer-run (a4 > 0) as captured by the expected value of future excess demand.

In the longer-run, the price behavior is determined as a dynamic equilibrium (if all nominal variables are growing at the same rate and there is an equilibrium on the good market):8

# **Equation** 2

Rather than the price level, we prefer to present the markup of price over costs in the long-run because it allows us to illustrate the differentiated effects of the sectoral inflation rate as well as of foreign prices on markups in each economic sector.

The above approach has been applied to four economic sectors using quarterly data over the period 1984-93: industry, agriculture, services, and commerce. The data was extracted from Argentina's National Accounts published by the Ministry of Economy, Argentina's National Institute of Statistics (INDEC), and the World Bank. The sectoral inflation rates were defined using the wholesale price and the consumer price indexes at three digit levels (see the statistical appendix for detail). The current excess demand in each economic sector has been defined as the deviation from sectoral GDP trend, while the expected value of future excess demand was calculated by the methodology used previously by Benabou and Rotemberg and Woodford.<sup>9</sup> Unit costs have been proxied by the average

- **s** For simplicity, the long run equilibrium excludes the feedback effect from wages to prices. 9 The expected value of future demand, xt = E(Yj=o &iYt+j±i), where a constant discount factor 6 = 0.9 is used for simplicity. We also used the same proxy for xt than others. It obtained by projecting sectoral
**Table 8.    Distribution of ad valorem components of MFN tariff rates in Russia in 2001-2003**

||**_2001_**||**_200_**|**_2_**|**_200_**|**_3_**|**_200_**|**_4_**|**_200_**|**_5_**|
|---|---|---|---|---|---|---|---|---|---|---|
|**_Ad_**<br>**_valorem_**<br>**_rate, %_**|_Frequency_<sup>_a_</sup>|_Percent_<sup>_b_</sup>|_Frequency_|_Percent_|_Frequency_|_Percent_|_Frequency_|_Percent_|_Frequency_|_Percent_|
|0|136|1.23|187|1.68|218|1.95|238|2.12|327|2.88|
|2.5|0|0|0|0|0|0|0|0|8|0.07|
|3|0|0|0|0|0|0|0|0|9|0.08|
|5|4,326|39.06|4,398|39.45|4,377|39.22|4,400|39.22|4,401|38.72|
|10|1,928|17.41|1,907|17.11|1,900|17.02|1,950|17.38|1,949|17.15|
|15|3,011|27.18|3,002|26.93|2,996|26.84|2,962|26.4|2,990|26.31|
|20|1,526|13.78|1,513|13.57|1,505|13.48|1,503|13.4|1,514|13.32|
|25|129|1.16|121|1.09|123|1.1|123|1.1|123|1.08|
|30|4|0.04|4|0.04|4|0.04|4|0.04|4|0.04|
|40|14|0.13|14|0.13|0|0|0|0|0|0|
|50|0|0|0|0|0|0|1|0.01|0|0|
|60|0|0|0|0|14|0.13|14|0.12|16|0.14|
|80|0|0|0|0|22|0.2|21|0.19|22|0.19|
|100|2|0.02|2|0.02|2|0.02|2|0.02|2|0.02|
|**_Total_**|11,076|100|11,148|100|11,161|100|11,218|100|11,365|100|
|_Notes:_|_a Number of l_|_ines at 10-_|_digit level_||||||||
||_b Percentage_|_out of total_|_number of pr_|_oduct line_|_s_||||||

23
Figure 7 Tax Revenue Effects of TIETP per Household by Decile in 2014 <!-- Start of picture text --> 316 387<br><!-- End of picture text --> <!-- Start of picture text --> 78<br><!-- End of picture text --> <!-- Start of picture text --> 0 ‐5 ‐11 ‐26<br>‐73<br>‐101<br>‐128<br><!-- End of picture text --> <!-- Start of picture text --> 0 ‐5 ‐11 ‐26<br>‐73<br>‐101 ‐128 ‐108<br>‐178<br>‐241<br><!-- End of picture text --> _Source:_ Authors’ depiction.

Table 9 shows the total PIT revenue effect, which was calculated by multiplying the average PIT burden per household and the total number of households (18,001,541 households in 2014). The total gross effect of TIETP was W 3.4 trillion, while the cost of TIETP reached W 1.9 trillion. The net gain was estimated at W 1.4 trillion (approximately US$1.3 billion), which increased PIT revenue by 4.2 percent as compared to baseline Scenario A without the intervention of TIETP. If the revenue increase in VAT and CIT is considered, the revenue impact of TIETP would be much larger.

Table 9 Total PIT Revenue Impact of TIETP

||**Avg. (thousands in KRW)**|**Total (billions in KRW)**|
|---|---|---|
|Scenario A|1,871|33,675|
|PIT<br>Scenario B|2,057|37,036|
|Scenario C|1,949|35,090|
|<br>GE (B‐A)|186|3,361 (10.0%)|
|Revenue<br>effect<br>TF (C‐B)|‐108|‐1,946 (‐5.8%)|
|NE (GE+TF)|78|1,415 (4.2%)|

_Source:_ Author’s calculation.

_Note:_ Numbers in parentheses under “Revenue effect” indicate the percentage increase from the revenue in baseline Scenario A.

39
- **Bruhn, Miriam and David McKenzie** , “In pursuit of balance: Randomization in practice in development field experiments,” _American Economic Journal: Applied Economics_ , 2009, _1_ (4), 200–232.

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26
are SMEs (see appendix tables A1).<sup>4,5</sup> At the onset of the global financial crisis in 2007, privately held firms, accounted for 30 percent of total assets and almost 40 percent of total employment in our sample. Moreover, about 60 percent of the firms, or about 160,000 firms, used long‐term debt at some point in the years preceding the financial crisis. Because we are interested in examining the evolution of debt use by firms over time, this subset of firms will constitute our main sample.

Our three main variables of interest are the ratio of total debt to total assets (TDTA), the ratio of long‐term debt to total asset (LTDTA), and the ratio of long‐term debt to total debt (LTDTD). The first two variables capture the extent to which firms finance their assets with debt and long‐term debt, respectively. The last variable captures the maturity composition of debt. A standard approach in the literature is to focus on a narrow definition of total financial debt, defined as the sum of short‐term financial debt (including trade credit),<sup>6</sup> plus long‐term financial debt (defined as the portion of long‐term debt maturing after one year). This approach has often been used in the literature, for instance by Rajan and Zingales (1995), because it is consistent with the focus on external finance in the theoretical corporate finance literature.<sup>7</sup>

> 4 We follow the World Bank Group Enterprise Survey definition, according to which a firm is defined as a small firm if it has between 5 and 19 employees, a medium firm if it has between 20 and 99 employees, and a large firm if it has more than 100 employees. In robustness tests, we will use a threshold of 250 employees to define a firm as an SME, consistent with the EU SME employment threshold.

> 5 The literature has shown that SMEs cover more than 50 percent of the formal workforce in developing countries and a very large share of economic activity on average (Ayyagari, Beck and Demirgüç‐Kunt (2007), Ayyagari, Demirguc‐Kunt, Maksimovic (2011)).

> 6 In our data, short term financial debt includes the portion of long‐term financial debt maturing within the year in addition to the debt with a maturity below one year.

> 7 See also Fan, Titman and Twite (2010). An alternative approach that we do not follow in this paper is to look at the total liabilities of the firm (excluding net worth), and to assess its maturity composition, by differentiating long‐term and short‐term liabilities. We do not follow this approach because liabilities other than net worth and financial debt typically include other items in addition to external debt financing, such as account payables (which are related to how firms manage transactions), pension liabilities, tax items or provisions. They may be unrelated to how firms are

9
Goos, M., A. Manning, and A. Salomons. 2014. “Explaining Job Polarization in Europe: RoutineBiased Technological Change and Offshoring”, _The American Economic Review_ , 104(8), pp. 2509-2506.

AfDB, ADB, EBRD, and IDB (African Development Bank, Asian Development Bank, European Bank for Reconstruction and Development, Inter-American Development Bank). 2018. “The Future of Work: Regional Perspectives”.

<mark>Maloney, W. and C. Molina. 2016. “Are Automation and Trade Polarizing Developing Country Labor Markets, Too?”. Policy Research Working Paper 7922. The World Bank.</mark> Matsuyama, K. 2007. “Beyond Icebergs: Towards A Theory of Biased Globalization”. _The Review of Economic Studies_ , 74, pp. 237-253.

Messina, J., A.M. Oviedo, and G. Pica. 2016. “Job Polarization in Latin America”. Mimeo, The World Bank.

Michaels, G., An. Natraj, and J. Van Reenan. 2014. “Has ICT Polarized Skill Demand? Evidence from Eleven Countries over Twenty-Five Years”. _The Review of Economics and Statistics_ , 96(1), pp. 60–77.

OECD. 2013. “Global Value Chains (GVCs): Indonesia”. Organisation for Economic CoOperation and Development. May 2013.

OECD. 2015. “Indonesia Policy Brief: Strengthening Indonesia’s Participation in Global Value Chains”. Organisation for Economic Co-Operation and Development. March 2015.

Pangestu, M., S. Rahardja, and L.Y. Ing. 2015. “Fifty Years of Trade Policy in Indonesia: New World Trade, Old Treatments”. _Bulletin of Indonesian Economic Studies_ , 51(2), pp. 239-261.

<mark>Poole, J.P., A. Santos-Paulino, M. Sokolova, and A. DiCaprio. 2017. “The Impact of Trade and Technology on Skills in Viet Nam”. ADBI Working Paper Series 770.</mark> <mark>Poole, J.P., and A. Santos-Paulino. 2017. “Computers, Trade, and the Changing Task Composition of the Vietnamese Labor Market”. Mimeo.</mark> Santos, I., S. Monroy, and M. Moreno. 2015. “Technological Change and Labor Market Disruptions: Evidence from the Developing World”. IZA conference mimeo.

World Bank. 2016. “Indonesian Economic Transformation and Employment. Policy Input for an Indonesian Job Strategy”.

22
headcount poverty rate, this indicates that a combination of poverty and inequality could be harmful for economic growth.

Regarding other control variables, provinces with more population density or larger shares of urban population or wage and non-farm income have faster growth. While the results with the population variables have opposite effects on poverty, the results with wage and non-farm income are consistent with those discussed earlier with Table 4. These suggest that the transitions from an agriculture-based economy toward wage-based and services-based economy could be beneficial for the country’s economic growth and poverty reduction. Our result is consistent with a key finding that m <mark>ovement of labor from agriculture to non-agriculture through structural transformation are a key driver behind economic development</mark> in recent studies for Viet Nam (Tarp, 2017; Liu _et al._ , 2022), and other countries (Deininger _et al._ , 2022).

As further robustness checks, we modify equation (2) by adding the interaction terms between lagged per capita expenditure (and income) and lagged values of control variables (state spending, investment spending, population density, share of urban population, share of population with highschool diploma and share of ethnic minority) and show the estimation results in Appendix A, Tables A.9 and A.10. We still find strong evidence on conditional β-convergence in both tables. Furthermore, the interaction terms of expenditure and income with poverty is negative and strongly statistically significant in both tables, and the interaction term of income and inequality is negative in Table A.10. These results suggest that, for the same level of economic development, higher levels of poverty and inequality are generally not conducive to economic growth.

# **4. Discussion and conclusion**

18
# **_Indirect Taxes_**

VAT is a major component of indirect taxes, contributing to about 36 percent of total tax collection in 2014. VAT is levied at a standard rate of 23 percent on most goods and services, but a reduced rate of 5 percent applies to certain food, books and magazines or 8 percent is imposed on supplies, such as medicines, hotel and catering services, certain transport and municipal services. There exists also a rate of 7% for products bought from farmers who pay the tax as a lump sum. A zero-rate applies to the intra-EU community supply of goods, exports of goods, some international transportation and related services. Usually, in order to apply zero VAT rate additional conditions need to be fulfilled. Some financial, medical and cultural services are exempt. In particular, small entrepreneurs with yearly revenues below 150 thousand zloty, are exempt from paying VAT and may not deduct the VAT paid on inputs. The VAT gap has been estimated to be between 30% and 50% of VAT collected (PwC, 2013).

Excise taxes contribute 3.4 percent of GDP and they are levied on goods that are deemed to be a harmful for health reasons. The Ministry of Finance in Poland announces every year the excise taxes that apply to products that might be harmful to health or environment. Goods subject to excise duty include energy products, alcoholic beverages and manufactured tobacco products, based on the legislation of the European Union.

# **Social spending**

Overall expenditures in Poland amounted to 42.1 percent of GDP in 2014, down from 45.5 percent of GDP in 2010 (Eurostat). A large part of public spending is dedicated to social protection (16.1 percent of GDP), while education (5.3 percent of GDP) and health (4.6 percent of GDP) are also relatively important. Total social spending in Poland amounts to 26 percent of GDP or 62 percent of total spending. The analysis presented below covers 51 percent of all government spending and 82 percent of social spending. In what follows, we describe the main highlights of existing social spending.

Spending on contributory pensions at 15.3 percent of GDP in 2014, accounts for the bulk of the social protection system. These benefits include old-age pensions which are by far the largest. In addition, there are several insurance schemes that deliver benefits, including disability and survivor pensions, maternity and unemployment benefits, as well as sickness allowances, funeral grants, family care, occupational and health rehabilitation allowances for insured individuals. In contrast, the non-contributory portion of the social protection system, accounts for only 0.9 percent of GDP in 2014 (Table 3). This figure includes spending on direct cash and near-cash transfers and can be thought of having three main pillars: family benefits, housing benefits, and social assistance.

8
||LAB_lE 3<br>impact ot Sovereignty|and Defaults|
|---|---|---|
|oras.tm|0. 981|0.317|
||JiS.5O5)|<br>(2.890)|
|S;ndicate|-0.006|-0.016|
||(-0.258)|<br>(-0.561)|
|Public|-0.131|-0.133|
||(-7.808)|<br>(-6.841)|
|Total Debt/GNP|0.915|**0.641**|
||(11.745)|<br>(5.204)|
|Reserves/GNP|-0.048|-0.164|
||(-3.053)|<br>(-5.670)|
|Debt Service/Export|s<br>0.004|0.003|
||<br>(1.034)|<br>(0.851)|
|IMF Standby|0.050|0.194|
||(1.977)|<br>(4.673)|
|Maturitv|0.091|0.086|
||(24.721)|<br>(18.757)|
|Investment/GNP|-1.150|-.395|
||(-8.535)|<br>(-2.083)|
|Real GNP Growth|0.040|-0.350|
||(-1.034)|<br>(-2.702)|
|Imports/GNP|-0.019|<br>-0.164|
||(-0.644)|<br>(-0.120)|
|Inflation|0.141|0.474|
||(1.629)|<br>(3.714)|
|Devaluation|-0.008|<br>-0.018|
||(-0.300)|<br>(-0.760)|
|Sovereign|-0.126||
||(-3.806)|<br>-|
|D0||0.109|
|||(4.059)|
|AdjR<sup>2</sup>|.40|.48|
|Nobs|2178|1332|

Notes: Estimated equation is (2), and<sup>the numbers in parentheses</sup><sup>**are 't' values.**</sup>