rafmacalaba/datause-encoder-data huggingface dataset:
# THE REVENUE IMPACT OF FISCAL REFORM

The 1994 fiscal reform had the desired effect of accelerating fiscal revenue collection. Before 1994, total fiscal revenue was growing between RMB 20 and 30 billion annually. After 1994, the annual fiscal revenue growth increased to more than RMB 150 billion on average. Figure 1 shows the trend of China’s fiscal revenue.

Figure 1: China’s fiscal revenue and its structure <!-- Start of picture text --> g<br>25000<br>20000<br>15000<br>10000<br>5000 national fiscal revenue<br>central fiscal revenue<br>sub national fiscal revenue<br>0<br>1978 1985 1990 1992 1994 1996 1998 2000 2002<br>fiscal year<br>fiscal revenue (100 million)<br><!-- End of picture text --> Source : Authors calculations The 1994 reform also had the intended effect of shifting fiscal revenues from sub-national governments to the central government. This impact can be seen clearly in Figure 1, where central revenues jump ahead of sub-national revenues for the first time in 1994. Subsequent changes in revenue-sharing rules have assured that central-government fiscal revenues continue to grow faster than sub-national fiscal revenues. Under the fiscal contracting system, the sub-national share of total fiscal revenue was very high, reaching a peak of 78.9% in 1993. After 1994, due to the newly introduced tax assignment system, and subsequent increases in the central 13
overhang, bail outs and capital flight. The first break in 1983 coincides with the assassination of the opposition leader Benigno S. Aquino, the trough occurs in 1985, and the second break takes place in 2001—a few years before the formal end of the slump. Although the duration of the decline phase is only two years, GDP per capita contracted by 18.63% in this short period of time. Last but not least, panel (d) shows an unfinished slump with a continuing decline in Madagascar. Madagascar grew rapidly for over a decade following independence from France in 1960 but then experienced a dramatic and ongoing collapse from 1971 onward. This roughly coincides with the transition of power from Philibert Tsiranana—Madagascar’s first president—to Didier Ratsiraka who fully seized power in 1975 by means of a coup. By 2002, the average Malagasy was about 50% poorer than in 1971. Madagascar’s GDP per capita did not recover its pre-slump level over a period of 31 years. At the end of the observed period, the decline is still ongoing and the provisional trough coincides with the censoring cutoff in 2014.

# **3 Characteristics of slumps**

We apply the sequential algorithm to the entire Penn World Table (v9.0, series _rgdpna/pop_ ) yielding 57 or 77 slumps between 1950 and 2014, depending on how permissive we are towards type I errors.<sup>8</sup> Supplementary Appendix S2 lists all episodes and Supplementary Appendix S4 provides summary statistics.

We detect many well-known growth collapses and deep recessions. Most slumps begin between the 1970s and the early 1990s. Several downbreaks occur following the oil shock in 1973–1974 and another peak occurs between 1979 and 1981 during the second oil shock and debt crisis of the early 1980s. The period between the 1970s and early 1980s is generally marked by heightened volatility, as has been documented in a number of studies (Easterly

> 8 We run the algorithm on all the PWT (v9.0) countries with a population of at least one million and at least 20 years of data. However, we discard some episodes that are driven by positive breaks in the slope coefficient but fail the negative growth criterion due to the presence of the AR( _p_ ) terms. A simple rule is applied to these cases, requiring that an actual contraction occurs within the range of the two estimated breaks, otherwise there is no slump.

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# **Stock Market and Investment: The Signalling Role of the Market**

In a market economy, the stock market performs three basic functions: (i) a source for financing investment; (ii) a signalling mechanism to managers regarding investment decisions; and (iii) a catalyst for corporate governance.

This paper focusses on the role of the stock market as a signal to managers in undertaking capital expenditures.' What do managers base their investment decisions upon? Do managers go by own perceptions (managerial perception) of fundamentals or market valuation (market perception)? In other words, what are the relative roles of managerial and market perceptions in capital expenditure decisions at the firm-level? In this paper, an empirical assessment of these issues are undertaken by looking at a panel of U.S. manufacturing firms, taken from Standard and Poor's Compustat database.

The paper is divided into two main sections. The first section lays out the analytical framework for the study with a detailed discussion of the Q theory of investment and its modifications. The second section reports the results of the empirical analysis and discusses the implications for developing countries.

In the literature, there have been two contrasting views regarding the role of the stock market with respect to investment decisions in the economy. One view argues that the stock market is essentially a sideshow. For instance, Bosworth (1975) has shown that if managers are concerned about the market value of the firm in the long-run while undertaking investment ' Samuel (1995) deals with the financing role of the market and Samuel (1996a) deals with the governance role of the market.
- Steiner, F. 2000, _Regulation, Industry Structure and Performance in the Electricity Supply Industry_ , Working Paper No. 238, ECO/WKP(2000)11, Economics Department, OECD, Paris, 12 April.

- Warren, T. 2000, ‘The impact on output of impediments to trade and investment in telecommunications services’, in Findlay, C. and Warren, T. (eds) 2000, _Impediments to Trade in Services: Measurement and Policy Implications_ , Routledge, London and New York, pp. 85–100.

- World Bank 2006, _Tunisia Agricultural Policy Review_ , Report No. 35239-TN, Washington DC.

- World Bank 2008, _Tunisia Global Integration: A New Generation of Reforms to Support Employment,_ World Bank, Washington DC.

- WTO (Word Trade Organization) 2005, _Trade Policy Review, Report by Secretariat, Tunisia_ , WT/TPR/S/152, WTO, Geneva.

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**Table 11: Aggregate change in livestock net revenue in Africa caused by each AOGCM scenario (billions US$/year)**

|**Variable**|**Total impact to**<br>**small farms**|<br>**Total impact to**<br>**large farms**|**Total impact to**<br>**all farms**|
|---|---|---|---|
|**2020**||||
|**Change _CCC**|+1.26|-5.63|-4.37|
|**Change _CCSR**|+2.13|-6.15|-4.02|
|**Change _PCM**|-0.22|-10.57|-10.79|
|**2060**||||
|**Change _CCC**|+2.77|-12.40|-9.63|
|**Change _CCSR**|+1.50|-14.55|-13.05|
|**Change _PCM**|+0.33|-13.75|-13.42|
|**2100**||||
|**Change _CCC**|+6.00|-14.01|-8.01|
|**Change _CCSR**|+7.88|+0.04|+7.92|
|**Change _PCM**|+1.61|-16.33|-14.72|

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_For labor or for divorce?_

# **1. Introduction**

One of the most persistent and salient features of labor markets in the Middle East and North Africa (MENA) region is that women participate significantly less than men despite substantial reduction of the gender education gap (Assaad et al., 2020) –the average female labor force participation rate in the region is a mere 18 percent (WDI, World Bank, 2021). For example, in Morocco only 23 percent of women participate in the labor market and this rate is even lower for countries like Jordan where it did not exceed 13 percent in 2021. Under the canonical collective household model, marriage markets and legislations governing divorce influence the labor supply of spouses and the intrahousehold decision process (Chiappori et al., 2002; Fernandez and Wong, 2014; Field et al., 2021). While a large body of literature has studied the consequences of the introduction of more liberal divorce laws on intrahousehold distribution of bargaining power and labor supply within the collective household labor supply framework (Chiappori, 1988; 1992; Apps and Rees, 1988), less is known about MENA region countries in this regard. Particularly in circumstances where traditional gender roles prevail as social norms and where women possess limited influence or bargaining power within the marriage, their choices regarding work may not be adequately acknowledged or facilitated (Alesina, 2013; Qian, 2008; Jensen, 2012; Heath and Mobarak, 2015; Jayachandran, 2015; 2021).

**Figure 1. Relationship between gender progressive laws and FLFP by Country**

<!-- Start of picture text --> 10 20 30 40 50<br>FLFP rate<br> MENA OECD East Asia Europe Central Asia<br> South Asia Sub-saharan Africa Latin America Fitted values<br>100<br>80<br>60<br>WBL_Index<br>40<br>20<br><!-- End of picture text --> Source: Authors from World Bank, Women, Business, and the Law (2023) database. Note: Used data comes from the World Bank’s time series on Women Business and the Law index (1971-2023) for 122 countries belonging to the MENA, OECD high-income, South Asia, Latin America, East Asia, Sub-Saharan Africa, and Europe and Central Asia regions. The latest year, 2023, is considered. The index scores are based on the average of each economy’s scores for the 8 topics included in the aggregate score: mobility, workplace, pay, marriage, parenthood, entrepreneurship, assets, and pension. The index scores range between 0 and 100 and a higher score indicates more gender equal laws. The corresponding values for female labor force participation rate for each country are from the World Bank, World Development Indicators database.

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formal manufacturing but higher output in informal manufacturing (see section 5). A survey of 1000 manufacturing establishments drawn from 10 Indian states revealed that managers would be willing to reduce their work force by 16-17 percent if there was greater labor market flexibility, this indicating the negative impact of labor regulation on firm productivity (Dollar, Iarossi and Mengistae 2001).

Of course, there are a number of areas where government regulation is called for. For example, in the area of finance, legal and regulatory institutions that protect investors and creditors from expropriation, are critical to engendering financial development. Glaeser, Johnson and Shleifer (2001) argue that in Poland, strict enforcement of the securities law by a highly motivated regulator was associated with a rapidly developing stock market. In contrast, in the Czech Republic, hands-off regulation was associated with a moribund stock market. La Porta and others (1998) find that common law countries provide investors and creditors with greater protection than do civil law countries, and this results in larger debt and equity markets (La Porta and others 1997) and faster economic growth (Levine 1998). Given that external finance becomes increasingly important as firms grow, identifying the set of institutions which support financial development in a given location is critical.

Nevertheless, it is frequently the case that removal of the impediments to entrepreneurship via regulatory change can be a powerful mechanism for attracting new firms to a location. As employment in a location increases various types of 2<sup>nd</sup> advantage kick in as a result. Thicker markets imply better access to inputs and customers, skilled workers and external finance become more available, and firms benefit from technological upgrading. The emergence of entrepreneurs as a powerful political class can also lead to demand for institutions which protect property and support contracting and finance. Stern (2003) argues that improvements in the investment climate can be a powerful means of engendering increasing returns to scale along these different dimensions.

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government officials receive side-payments to either select a contract from a particular firm or to process documents of the operating firm. This results in higher unit costs and allocative inefficiency if contracts are not awarded to the most competitive firm. Second, individuals working for companies in the construction sector might inflate costs and use part of of these resources to extract side payments for themselves. The higher unit cost, in turn, decreases the likelihood of the project to be selected ex-ante by lowering the net present value or rate of return. Third, companies might not respect the contracted standards by using fewer or inferior materials. Here we only focus on the first level.<sup>7</sup>

# **II Data**

We use unit cost data from the Roads Cost Knowledge System (ROCKS), Version 2.3, developed by the World Bank’s Transport Unit.<sup>8</sup> Motivated by the lack of comparable information on costs of road work activities across countries, the database was started in 2001 with the aim of developing “an international knowledge system on road work costs – to be used primarily in developing countries – to establish an institutional memory, and obtain average and range unit costs based on historical data that could ultimately improve the reliability of new cost estimates and reduce the risks generated by cost overruns” (World Bank 2006). The focus of this section is on describing the data; we discuss issues due to selection in detail in the next section. The data is collected in collaboration with road agencies in the respective countries using information from Implementation Completion Reports, Pavement Management Systems Review Reports, Works Contracts, Appraisal Reports, and Highway Development and Management Studies. It includes road work activities financed

> 7It is also worth highlighting several issues relevant to the procurement of roads that we do not consider in our simple model. First, the market structure of the road construction sector and tender procedures affect how many firms will submit bids for a project, thereby determining _ex-ante competition_ and the value of bids (Li and Zheng 2009). Second, if firms collude in the tendering phase, they can affect the price of the road contract (Pesendorfer 2000). Third, once a government has signed a contract with a firm for a road construction project, the firm can extract rents from the government, a problem referred to as hold-up in the literature (Board 2011). In the absence of data on the market structure, values of submitted bids for work activities, and the difference in costs between contracted and actual costs for each work activity, we are not able to uncover these effects. The main rationale for the simple cost minimization framework is to inform our way of thinking about the deeper determinants of costs and input prices in an economy and to serve as a guide for the estimation. See Moavenzadeh (1978) for a discussion of how the construction sector generally differs from other sectors.

> 8For access to the data see http://go.worldbank.org/ZF1I4CJNX0.

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# _Table 4: Estimating the gains from trade in health services for the US_

|_Procedure_|_US inpatient_<br>_price ($)_|_US_<br>_inpatient_<br>_volume_|_US outpatient_<br>_price ($)_|_Estimated US_<br>_outpatient_<br>_volume_|_Average of three_<br>_lowest foreign_<br>_prices including_<br>_travel cost ($)_|_Savings if 10% of_<br>_US patients_<br>_undergo surgery_<br>_abroad instead of in_<br>_the US ($)_|
|---|---|---|---|---|---|---|
|Knee surgery|10,335|399,139|4,142|60,000|1,236|380,604,366|
|<br>Shoulder Arthroplasty|5,940|23,300|7,931|N/a|2,204|8,704,809|
|<br>TURP|4,127|111,936|3,303|88,064|2,385|27,581,317|
|Tubal Ligation|5,663|78,771|3,442|621,229|1,248|171,065,574|
|<br>Hernia Repair|4,753|40,553|3,450|759,447|1,608|152,655,706|
|<br>Skin lesion excision|6,240|21,257|1,696|1,588,884|812|151,952,860|
|Adult Tonsillectomy|3,398|17,251|1,931|102,749|1,010|13,588,218|
|<br>Hysterectomy|5,783|640,565|5,420|N/a|1,869|250,704,845|
|<br>Haemorrhoidectomy|4,945|12,787|2,081|137,213|781|23,160,663|
|<br>Rhinoplasty|5,050|7,265|3,417|N/a|1,906|2,284,315|
|<br>Bunionectomy|6,046|3,139|2,392|41,507|1,487|5,186,290|
|<br>Cataract extraction|3,595|2,215|2,325|1,430,785|1,133|171,078,116|
|Varicose vein surgery|7,065|1,957|2,373|148,043|1,393|15,618,521|
|<br>Glaucoma procedures|3,882|-|2,292|75,838|1,017|9,670,440|
|<br>Tympanoplasty|4,993|754|3,347|149,246|1,261|31,408,685|
|Total savings||||||1,415,264,725|

_Sources:_ Health care Cost and Utilization Project (H-CUP) database, 2002, Vanbreda International, and authors’ calculations. An “N/a” denotes that data was not available. Patient volume data pertain to 2002, while the prices pertain to 2004.

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Although we find it plausible that the Thai Village Fund yields net benefits, we recognize that this result is fragile. If benefits are smaller than indicated here – Chandoevwit and Ashakul (2008) find no significant effects on income or expenditure – or if the costs are higher, especially loan losses, but also the opportunity costs of funds, then one could conclude that the VF fails the basic test of cost-benefit analysis.

Our analysis weighs all costs and benefits equally; if benefits accruing to poorer households are given more weight than benefits accruing to others, then the Village Fund is likely to look more attractive, because it is VF loans to the poor that appear to have the largest measurable impact (Boonperm et al. 2011).

|**Table 29. Cost-Benefit Analysis of V**|**illage Fun**<br>Median|**d Lending**<br>Mean|Comments|
|---|---|---|---|
||_per 100 b_|_aht lent_||
|**1. Costs**||||
|Administrative:||||
|Honoraria to committee members|1.1|1.1|Overly generous?|
|Imputed value of volunteering|0.0|0.4|May not be a true cost; volunteers get psychic income.|
|Value of social contributions (goodwill)|0.4|0.5|Possibly overstated; not all VFs make such subsidies.|
|Material costs (computer use, etc.)|0.0|0.0|Understated; does not include VF HQ, stationery.|
|Capital costs:||||
|Opportunity cost of capital provided|4.0|4.0|May be too low (not risk-adjusted).|
|Interest paid for BAAC/GSB loans|0.9|0.9||
|Interest paid to village savers|0.4|0.6||
|Dividends paid to villagers|0.4|0.7|May be too high; sharing VF rent within village?|
|Loan losses|2.1|2.1||
|**Total costs**|**9.2**|**10.2**||
|**2. Benefits**||||
|Return based on income|13.5|18.0|Plausible a priori, but estimates not robust.|
|Return based on consumption|27.2|33.7|Robust,but overstates economic contribution.|
|**3. Net return**||||
|Based on income|4.3|7.8||
|Based on consumption|18.0|23.5||
|**Memo items**||||
|Income per h’hold per month, baht|12,074|16,957|From 2009 SES.|
|VF return, 1.4% of income, baht/year|2,028|2,849|Return from Boonperm et al. (2011), Table 5|
|95% CI, income-based return, %|-21 to 48|-27 to 64||
|Consumption per h’hold/month, baht|9,703|12,677|From 2009 SES.|
|VF return, 3.5% of consumption, baht/yr|4,075|5,324|Return from Boonperm et al. (2011), Table 5|
|95% CI, consumption-based return, %|4 to 50|5 to 62||
|Average amount borrowed from VF|15,000|15,790|From 2009 SES.|

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32

- Figure 9: _Share of Consumer Services (Excluding Housing for USSR) in Value Added_ See also note for Figure 8. Note: The housing sector in the USSR has been highly subsidized. At established prices its share is about _0.5_ percent of GDP. At factor cost, with adjustments made by the CIA, the share equals to 5-6 percent of GNP, which given the low availability of housing in the USSR is probably upward biased in the international comparison.

- Figure 10: _Share of Government, Health, Education, Military, and Scientific Services in Value Added_

- For OECD, data include all services produced by the government as well as non-government education and health services

- Figure 11: _Share of Government, Health, Education, and Scientific Services in Value Added_ See note for Figure 10.

- Figure 12: _Share of Government, Health, Education, Military Services in Value Added_ See note for Figure 10.

- Figure 13: _Share of Government, Health, and Education Services in Value Added_ See note for Figure 10.

# B. Share of Services in Employment: the USSR and OECD

All data refer to civilian labor force. The Soviet data are for full-time equivalent of the employed.

- Figure 15 _Share of Total Services in Employment_

- Figure 17: _Share of Transport and Communication Services in Employment_

- Figure 19: _Share of Trade, Restaurant, and Hotel Services in Employment_ Soviet data are without hotels. They are included in consumer services.

- Figure 20: _Share of Wholesale and Retail Trade in Employment_ Soviet data include restaurants.

- Figure 22: _Share of Banking and Insurance Services in Employment_

- Figure 23: _Share of Housing and Consumer Services in Employment_ OECD data do not include housing. For employment, it is not possible to separate housing for the USSR.
Figure A1: Survey period in context–contd.

<!-- Start of picture text --> CIV COL<br>80 0 100<br>0<br>-20 60 -20 80<br>-40<br>-40 60<br>40<br>-60<br>-60<br>40<br>20<br>-80 -80<br>20<br>-100 0 -100<br>03/01 05/01 07/01 09/01 03/01 05/01 07/01 09/01<br>CYP GAB<br>100 0 80<br>0<br>80 -20<br>-20 60<br>60 -40<br>-40<br>40 -60 40<br>-60<br>-80 20 -80<br>20<br>-100 0 -100<br>03/01 05/01 07/01 09/01 03/01 05/01 07/01 09/01<br>GEO GRC<br>0 100<br>80<br>-20<br>80<br>60<br>-40<br>60 0<br>-60 -20<br>-40 40<br>40<br>-80 -60<br>-80<br>-100 20 -100 20<br>03/01 05/01 07/01 09/01 03/01 05/01 07/01 09/01<br>GTM SLV<br>0 100 0 100<br>-20 80 -20 80<br>-40 60 -40<br>60<br>-60 40 -60<br>40<br>-80 20 -80<br>-100 0 -100 20<br>03/01 05/01 07/01 09/01 03/01 05/01 07/01 09/01<br>Stringency of<br>Mobility around<br>Period of interview lockdown<br>transit stations<br>restrictions<br>Google mobility Stringency of Google mobility Stringency of<br>index (baseline = 0) lockdown measures index (baseline = 0) lockdown measures<br>Google mobility Stringency of Google mobility Stringency of<br>index (baseline = 0) lockdown measures index (baseline = 0) lockdown measures<br>Google mobility Stringency of Google mobility Stringency of<br>index (baseline = 0) lockdown measures index (baseline = 0) lockdown measures<br>Google mobility Stringency of Google mobility Stringency of<br>index (baseline = 0) lockdown measures index (baseline = 0) lockdown measures<br><!-- End of picture text --> Data from Google (2020) for the mobility trends and Hale et al. (2020) for the lockdown restrictions. The mobility trends are smoothed using 7-day moving averages.

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