rafmacalaba/datause-encoder-data huggingface dataset:
- 70 -

We could also calculate the marginal effective personal tax rate tp as discussed earlier. However, given our open economy arbitrage assumption, it would be irrelevant for evaluating investment incentives. Its effect is felt entirely on the saving side of the domestic capital market. As mentioned, given the absence of taxation of capital gains and the imputation of corporate taxes to domestic savers, the effective personal tax rate would be near zero for equity funds. Indeed, saving through purchases of new equity could be subsidized given that the corporate tax rate can exceed the personal tax rate so the imputation more than offsets any personal taxes owing on dividends. However, the marginal effective personal tax rate could be substantially larger for interest since interest is not only fully taxed, but it is taxed in nominal terms. Therefore, the tax system gives a sizeable incentive for domestic residents to hold equity over bonds. Since the corporate tax system does precisely the opposite, there is a net incentive to import debt capital and export equity capital. The reduction in the corporate tax rate by 10 percentage points with the tax reform of 1989 reduces the magnitude of this relative financing incentive for equity but not its direction.

Some marginal effective corporate tax rate calculations are presented for the three cases in Tables 1, 2 and 3 respectively. Each Table reports tc for machinery for five consecutive years under the pre-1989 and post-1989 tax systems. The main differences in the tax systems are that the rate is reduced from 45% to 35% and the deferral of depreciaiton allowances for pioneer firms is eliminated by the tax reform. The data used in the Tables also differs from one to another. For the fully taxpaying firm, actual data for the years 1983-87 are used for financial variables, while for the tax loss and pioneer firms, 1983 data are used. For all examples, tc is calculated separately for debt-financed and retained-earnings fnanced investments<sup>49</sup> as well as for a weighted combination of the two, where the weights were computed from Kuala Lumpur Stoc& Exchange unpublished data. Rates of return on equity were also calculated from the same source using the return to shareholders' fund. Corporate lending rates were not available so a base case of 12% was used for illustrative purposes. Actual inflation rates were used as expected ones and therefore perfectly anticipated. Again, it should be stressed that these calculations are intended to be illustrative only. A summary of results for each of the cases follows.

# _a. Taxpaying Non-Pioneer Firms_

As the first column of Table 1 indicates, tc is consistently negative for debt-financed investments owing to the deductibility of nominal interest payments. Fluctuations from year to year are due to 49 From **the** point of view of **the** corporation, the tax system affects new equity and retained **eanings in the** same way.
paper was 6 months before these trade reforms and that the effect presented in the graphical periodic coefficients shows that response was mostly after this period, we test the effect of these trade policies on FDI. This is also in line with the literature on complementary institutional reforms in addition to FDI reforms to the extent that these regulatory changes improved the trade regime or were perceived to do so.

We use the same methodology, with the reform period adjusted to November 2021 instead of May 2021, and focus on the all the manufacturing sectors, and the fully liberalized non-commodity sectors.

We find that realized FDI in all manufacturing sectors increased by 103.2 percent following these trade reforms (Table 7). In fully liberalized non-commodity sectors, realized FDI also increased by 21.2 percent after the trade reforms compared to the period before the trade reforms. Figure 7 shows the period-by-period coefficients.

While the caveat should be noted that the post-trade reform period is even shorter than that for the investment reform, this may signal the importance of complementary trade reforms and that the shift between the levels of liberalization is still important. Some of the trade reforms were being implemented after they were enacted, which may have had mixed effects. Crucially, this analysis does not distinguish which of these (many) trade regulatory changes may have been the key to this response as that is beyond the scope of this analysis.

Table 7: Event study results of the response of Realized FDI to trade policy changes in November 2021

|ATET|ATET|ATET|
|---|---|---|
|All Manufacturing Sectors (1vs0)<br>1.032***<br>(0.0796)|||
|100 % (1vs0) Liberalized Non-Commodity Sectors|0.212***<br>(0.0282)||
|Non-Fully Liberalized Non-Commodity Sectors (1vs0)||-0.197***<br>(0.0275)|
|Observations<br>29,913|39,169|39,169|
|Robust standard errors in parentheses *** p_<_0.01,<br>Source: Author estimations|** p_<_0.05|, * p_<_0.1|

20
**Table 5: Inter-Rater Reliability (ICC using one-way random effects model)**

|**Level 1**|||**Level 2**|||
|---|---|---|---|---|---|
|||Mean diff.|||Mean diff.|
||ICC|(abs. val.)||ICC|(abs. val.)|
|**SDI**||||||
|Share of time teaching|**0.95**|0.04|Teacher interacts with students as a group|**0.86**|0.08|
|Share of time teaching and learning|**0.75**|0.15|Teacher interacts with a small group of children|0.00|0.04|
|Good teacher demeanor|**0.87**|0.09|Teacher interacts with children one on one|**0.33**|0.10|
|Good pedagogical practice|**0.73**|0.07|Teacher reads, lectures, or demonstrates to the pupils|0.00|0.03|
|Classroom environment|**0.64**|0.23|Teacher supervises pupils writing on the board|**0.95**|0.02|
|Materials and infrastrucutre|**0.46**|0.07|Teacher leads kinesthetic group learning activity|**0.42**|0.02|
|Use of materials|**0.84**|0.10|Teacher writing on blackboard|**0.71**|0.06|
||||Teacher listening to pupils read/recite|0.00|0.03|
||||Teacher waiting for pupils to complete task|**0.72**|0.07|
||||Teacher testing students in class|0.00|0.04|
||||Teacher maintaining discipline in class|0.00|0.00|
||||Teacher in class, not teaching|0.00|0.01|
||||Teacher not in class, learning activity ongoing|**0.93**|0.01|
||||Teacher not in class, no learning activity ongoing|**0.96**|0.03|
||||Good Teacher Demeanor|**0.87**|0.09|
||||Good Pedagogical Practise|**0.73**|0.07|
||||Classroom Environment|**0.64**|0.23|
||||Availability of materials|**0.46**|0.07|
||||Use of materials|**0.84**|0.10|
|**Stallings**||||||
|Share of time teaching|**0.77**|0.08|Teacher involved in reading activity|**0.79**|0.01|
|Share of time teaching and learning|**0.63**|0.17|Teacher involved in lecture activity|**0.92**|0.04|
|Materials and infrastrucutre|**0.52**|0.04|Teacher involved in discussion|**0.79**|0.07|
|Classroom environment|**0.63**|0.21|Teacher involved in practice activity|0.00|0.02|
||||Teacher involved in class work activity|**0.77**|0.07|
||||Teacher giving instructions on blackboard|**0.86**|0.01|
||||Teacher giving verbal instructions to students|**0.75**|0.01|
||||Teacher involved in classroom management related act|**0.49**|0.01|
||||Teacher involved in classroom management related act|**0.79**|0.02|
||||Teacher not present in the classroom|**0.84**|0.04|
||||Materials and infrastrucutre|**0.52**|0.04|
||||Classroom environment|**0.63**|0.21|

continued...

42
- **44.**

Table (5.6), and assume that the government fixes its stock of reserves. The aggregate outcomes for real GDP, real private consumption and the price level are: Table 5.9: Base Simulation with Government SpendiLng not Entering Infrastructure g/

||1983|1984<br>1|985|
|---|---|---|---|
|Real GDP>/|318.6 (386.5)|324.1 (396.2) 334.6|(397.4)|
|Real private||||
|consumption|219.9 (267.2)|247.4 (302.6) 258.7|(307.3)|
|Price indexq/|121.8 (100.0)|200.5 (162.3) 260.0|(220.1)<br>w|

- n/ The numbers in parenthesis correspond to the results of Table (5.6).

- k/ Real GDP is based upon the price index for 1983 generated by the bate case example of Table (5.6).

- g/ The price index in the base case example is set to be equal to 100 in 1983.

We thus notice that the assumption of nonproductive government leads to much lower levels of real GDP and private consumption than are evident in the base case. In addition, the overall price index is 18.1 percent higher by 1985 than before, indicating the impact on aggregate outcome caused by the incorporation of the infrastructure elasticity of 0.05. Finally, the domestic consumer's utility level, that was 463.5 in the original example, has fallen to 275.3, corresponding to the sharp decline in private consumption.
# **References:**

Albrecht, J., W., Navarro, L. and Vroman, S. B., (2006) "The Effects of labor Market Policies in an Economy with an Informal Sector," IZA Discussion Paper No. 2141 Antman, F. and D. J. McKenzie (2007) “Earnings Mobility and Measurement Error: A Pseudo-Panel Approach” _Economic Development and Cultural Change_ ,University of Chicago,56(1):125-161.

Blanchard, O. J. & Diamond, P., (1992). "The Flow Approach to Labor Markets," _American Economic Review_ , vol. 82(2), pages 354-59, May.

Baker, M. (1992) “Unemployment Duration: Compositional Effects and Cyclical Variability,” _American Economic Review_ , 82(1): 313-321.

Boeri T., Garibaldi, P. (2006), "Shadow Sorting" CEPR discussion paper.DP5487.

Boeri T., Garibaldi P. (2001) "Shadow Activity and Unemployment in a Depressed Labor Market". IGIER Working Paper No. 77, Bocconi University, IGIER, Milano, Italy. 13 June.

Bosch, M. (2004) "Start Up Costs, Informality and Policy Complementarities". Mimeo LSE.

Bosch, M. and W. F. Maloney (2006) “Gross Worker Flows in the Presence of Informal Labor Markets: the Mexican Experience 1987-2002” World Bank Policy Research Working Paper 3883.

Bosch, M. and W. F. Maloney (2007) “Comparative Analysis of Labor Market Dynamics Using Markov Processes: An Application to Informality,” IZA Discussion Paper 3038, World Bank Policy Research Working Paper 4429.

Bosch, M., Goni E., and W. F. Maloney (2007). "The Determinants of Rising Informality in Brazil: Evidence from Gross Worker Flows," IZA Discussion Papers 2970, Institute for the Study of Labor (IZA), World Bank Discussion Paper 4375.

De Paula, A and J. Sheinkman (2007), The Informal Sector," UCLA Department of Economics, Mimeo De Soto, H. (1989). _The Other Path: The Invisible Revolution in the Third World._ New York: Harper and Row.

Elsby, M., G. Solon, and R. Michaels (2007) “The Ins and Outs of Cyclical Unemployment,” NBER Working Paper No. 12853, January 2007.

Ericson, R. and A. Pakes (1992), “An Alternative Theory of Firm & Industry Dynamics”, Cowles Foundation Paper 1041 26
other related ministries. In China, the Ministry of Water Resources has great powers, but also has an irrigation and flood control focus and experiences difficulty in managing relationship with other ministries and the provinces. Such difficulty, however, are related to the power and control over water planning and implementation conferred upon the organization by the government. If WARPO is given the mandate and legally empowered to examine and approve water related activities of all government and private organizations, it would have the necessary impact that is currently not there. The design of the organization could be further enhanced by bringing into it the element of participative management from all subsectors which will provide further legitimacy to its actions.

In the management of overall water resources in Bangladesh WARPO's four major functions would be:

1. Planning: National, regional and basin planning with overall assessment of water supply and demand in the country.

2. Overall Management of Water Resources: This would involve management of both supply and demand. Supply management necessitates medium and longterm planning for new development and replenishment of fresh water resources. Demand management would include direct measures of controlling water use, to indirect measures that affect voluntary behavior (market mechanism, financial incentives, public awareness programs).

3. Monitoring, Evaluation and Data Collection: Water resources data, in particular hydrological and hydrogeological data, are essential for planning and designing water programs. In Bangladesh, there are specialized government agencies that collect, process and transmit some of these data, but the latter is too disjointed, poorly recorded and inadequate for comprehensive planning.

4. Regulations: The regulatory aspects of water resource management often get lost in the bureaucratic maze of government agencies. Without one central body, systematically looking through various regulatory requirements and working like a watch dog to measure compliance by various entities, it would be very difficult to bring discipline in the sector's management. The National Water Policy Council sets the agenda for water use, conservation, and environmental renewal. However, it needs a mechanism for constant evaluation and updating of policies, something that should become the mandate of WARPO as the advisory body for the National Water Council. Rules for administering water rights, land-use rights, environmental quality standards, quality of service standards (e.g. for urban water quality) must be framed and administered by WARPO.

WARPO's mandate could be restated to cover the specific activities mentioned above. This could easily be done with minimal dislocation, through reformulation and addition of a few specific mandates.

27
We begin with Table B1 (Appendix A.2) where we explore heterogeneity of members’ education with employment type and sector. In the spirit of the analysis undertaken in Section 3.2.2, we ask whether employment in select non-farm occupations is sufficient to positively affect household consumption, or are there other complementary factors such as educational or district characteristics which require to be satisfied.

The odd numbered columns in Table B1 (Appendix A.2) explore heterogeneity by whether the household has any literate member; even numbered columns do the same for members with secondary education or better. The results suggest that education acts as a “force multiplier” with regard to household consumption. Thus, while households with a member employed in non-farm salaried work have on average 4 percent higher monthly per capita consumption, this increases by an additional 10 percent if the household also has a secondary educated member [column (2)]. On the other hand, employment in the service sector has a positive impact on household consumption if the household has a literate or secondary educated individual [columns (3) and (4)]. However, education is unable to reverse the negative impact of casual non-farm work on household consumption: households with some educated member, and also with some member engaged in casual non-farm work see their monthly per capita consumption fall by an additional 8 percent. Surprisingly, employment in the manufacturing sector has no impact on rural households’ consumption, even when the household has a secondary educated member. This again points to the relatively unskilled nature and low income generating potential of rural manufacturing.

Table B2 (Appendix A.2) shows that there is limited heterogeneity in the impact of rural non-farm employment on household consumption across district characteristics. Thus, the presence of a non-farm salaried worker in the household continues to have a robust positive effect on monthly per capita consumption for rural households, regardless of whether the district has a relatively high urban population, manufacturing workers, or public employment. We also find no evidence of heterogeneity in non-farm employment’s effect on rural consumption across district bank branches, suggesting a limited role for aggregate supply-side factors such as infrastructure.

# **3.4 Barriers to the Performance of Rural Non-Farm Enterprises**

Panel B of Table 1A shows that 60 percent of rural non-farm workers are either self-employed, or engaged as casual workers. This forms the motivation to briefly consider the performance of rural non-farm enterprises, and examine the impact of constraints faced by such enterprises on their performance. We exploit the rich enterprise level data provided by the Survey on Unincorporated Enterprises, undertaken in 2010-11 by the NSS. As described in Section 23
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schooling, or between 0 and 6 years of schooling (omitted variable in the regression); _Pric_ is equal to 1 if complete primary school (7 years of schooling); _Seci_ is equal to 1 if individual did not complete secondary school (between 8 and 11 years of schooling); _Secc_ equals 1 if individual has complete secondary school (12 years of schooling); _Supi_ equals 1 if individual did not complete university (or college) (between 13 and 16 years of schooling); and _Supc_ equals 1 if individual completed university (17 or more years of schooling). The returns to schooling by level are derived from: where _SPric_ , _SSeci_ , _SSecc_ , _SSupi_ and _SSupc_ are the total number of years of schooling for each successive level of education.

This model has two important assumptions: (1) the wage differential among workers with different levels of education is constant throughout the whole period; and (2) the only costs of continuing studies are foregone wages during that period. The models will be estimated using OLS.

6
section IV, we set the structural price of oil to US$50/barrel, which is the estimated unconditional mean of oil prices from 1960 to 2020. The actual path of commodity prices can be set to any value. Again, in section IV, we analyze the consequences of an increase in oil prices from US$50 to US$80/barrel. The default data source for commodity prices is the World Bank’s Commodities Prices Dataset (WB-CPD– _The Pink Sheet_ ), although other sources are available (e.g., USGS and BP-Energy). Also, the structural production of resources is usually assumed to follow N-year moving average of actual production.

Discoveries of natural resources are calibrated using data on annual production and reserves of the resource good , taken from the BP-Energy (for energy industries) and the USGS (for mining). The time series of discoveries of good in ii period is computed as the change in reserves from period to plus ii production in period (as in equation (3)). In the baseline, the trajectory of tt tt−1 tt discoveries of good from 2020 to 2050 can be set to match the historical average tt over the past 20 years. Naturally, predicting future discoveries of natural resources ii is no trivial task and using historical averages can be misleading. In this case, country-specific data based on experts’ knowledge should be used when available.

The LTGM-NR requires paths for future TFP growth in each sector and industry. TFP data at the industry level is usually unavailable for most developing countries. A simple approach is to assume that TFP growth is homogenous across sectors. In this case, we can set TFP growth in each sector/industry equal to the average aggregate TFP growth over 2000-2019, from PWT 10. When available, the user should use information on sectoral TFP growth.<sup>35</sup> In the Default submodel, private- and public-sector investment data are taken from IMF-FAD, which decomposes total investment into private and public from 1960 to 2017. The paths for private investment, , and the exogenous component pp tt ıı̅

> 35 For example, the Chilean 2016 Annual Report of the National Productivity Commission documents a large heterogeneity of TFP growth across the copper and non-copper sectors over 20002015, with an average fall of one percent in the copper sector and average growth of 1.4 percent in the non-copper sector.

23
|CG Rep. Health Sector Project<br>MoulayDriss Zine Eddine El Idrissi|
|---|
|CG Rep. Health Sector Project<br>MoulayDriss Zine Eddine El Idrissi|
|AUC: BuildingCapacityfor a Results-Oriented Engagement betweenWaleed Haider Malik|
|AUC: BuildingCapacityfor a Results-Oriented Engagement betweenWaleed Haider Malik|
|GABON - SUSTAINABLE MANAGEMENT OF CRITICAL WETLANDS ECOSalimata D. Follea|
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|GABON - SUSTAINABLE MANAGEMENT OF CRITICAL WETLANDS ECOSalimata D. Follea|
|GABON - SUSTAINABLE MANAGEMENT OF CRITICAL WETLANDS ECOSalimata D. Follea|
|GABON - SUSTAINABLE MANAGEMENT OF CRITICAL WETLANDS ECOSalimata D. Follea|
|GABON - SUSTAINABLE MANAGEMENT OF CRITICAL WETLANDS ECOSalimata D. Follea|
|GABON - SUSTAINABLE MANAGEMENT OF CRITICAL WETLANDS ECOSalimata D. Follea|
|GABON - SUSTAINABLE MANAGEMENT OF CRITICAL WETLANDS ECOSalimata D. Follea|
|GABON - SUSTAINABLE MANAGEMENT OF CRITICAL WETLANDS ECOSalimata D. Follea|
|GABON - SUSTAINABLE MANAGEMENT OF CRITICAL WETLANDS ECOSalimata D. Follea|
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|GABON - SUSTAINABLE MANAGEMENT OF CRITICAL WETLANDS ECOSalimata D. Follea|
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|SafetyNet and Skills Development<br>Endashaw Tadesse Gossa|
|SafetyNet and Skills Development<br>Endashaw Tadesse Gossa|
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|Flood EmergencyProject<br>Jorge Trevino|
|Flood EmergencyProject<br>Jorge Trevino|
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|Flood EmergencyProject<br>Jorge Trevino|
|Flood EmergencyProject<br>Jorge Trevino|
|Flood EmergencyProject<br>Jorge Trevino|
|Flood EmergencyProject<br>Jorge Trevino|
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