rafmacalaba/datause-encoder-data huggingface dataset:
International Monetary Fund. Trade liberalization dates come from Wacziarg and Welch (2008) who extended and refined the database of Sachs and Warner (1995).<sup>13</sup> The data on Legal System and Property Rights used in Section 6 come from the Economic Freedom Database by Fraser Institute. The index captures the degree of protection of property rights in the countries for the year 1980. The index varies from 0 to 10, with the lower number corresponding to a lower level of investor protection. Gwartney, Lawson, and Norton (2008) provide more details. The alternative measures of legal environment used in Online Appendix E (Efficiency of Judicial System, Rule of Law, Risk of Expropriation, Repudiation of Contracts by Government, and Investor Protection - an average of the three previous measures) are based on La Porta et al. (1998). The original sources of data for these alternative measures are from Business International Corporation and International Country Risk Guide (see La Porta et al. 1998 for details).

# **3.4 Preliminary evidence and descriptive statistics**

Figure 1 and Figure 2 show Kaplan-Meier survival functions capturing the probability of a new export spell to survive after year 1,2, etc. Given the annual frequency of the data, the survival probability in the first year is one by default. Both figures focus on the average export survival rate for products that are in the 25th and 75th percentile of distance to comparative advantage, i.e. products that are close versus far away from the comparative advantage of the exporting country. Only countries that did liberalize during the period 1980-1997 are included. For these countries, Figure 1 reports the survival rate before and Figure 2 the survival rate after the event of stock market liberalization.

The comparison of Figure 1 and Figure 2 reveals that the overall export performance of countries improves after they allow foreign investors to acquire equity stakes in domestic companies - both survival functions move upwards. However, this effect is not uniform across products. The exported products that do correspond to the comparative advantage of the liberalizing countries benefit disproportionately more from the entry of

> 13 Sachs and Warner (1995), define a country as open to trade if it meets _none_ of the following criteria: Average tariff rates of 40 percent or more; Nontariff barriers covering 40 percent or more of trade; A black market exchange rate at least 20 percent lower than the official exchange rate; A state monopoly on major exports; A socialist economic system. Wacziarg and Welch (2008) rely on additional sources to identify the dates of abolishment of export marketing boards and the dates when multiparty governance systems replaced communist regimes.

11
<!-- Start of picture text --> 70<br>8. "I constantly fear<br>unconstitutional government 60<br>changes (i.e. coups) that are<br>accompanied by far-reaching 50<br>policy surprises with significant<br>impact on my business."<br>40<br>To what degree do you agree<br>with this statement?<br>30<br>(1) fully agree [L*<br>(2) agree in most cases 0 20<br>(3) tend to agree<br>(4) tend to disagree n<br>(5) disagree in most cases D 10<br>(6) strongly disagree _<br>does not apply<br>World LDC DC SSEA MNA CEE LAC SSA cis<br><!-- End of picture text -->

## **Percentage of firms who ticked (1), (2), or (3) for question 8**

The fear of business disruption due to irregular government changes is highest in Africa, the CIS and MNA where over 60 percent of entrepreneurs say their businesses would significantly be impacted. In Latin America, though it has a history of coups, this problem is perceived as relatively small.

# _Question 9. Theft and Crime_

Theft and crime indicate that property rights are not properly enforced. However, businessmen can sometimes find ways to protect themselves from this particular uncertainty by hiring private protection agencies. Therefore this question directly asks whether theft and crime substantially increase the cost of doing business.

16
**Figure 4: Market Concentration Ratios in Pensions and Annuities Herfindahl and Share of Three Largest Firms, 1988-05**

<!-- Start of picture text --> 2500 100%<br>90%<br>2000 80%<br>70%<br>1500 60%<br>50%<br>1000 40%<br>30%<br>500 20%<br>10%<br>0 0%<br>1988 1990 1992 1994 1996 1998 2000 2002 2004<br>AFP Herfindahl Annuity Herfindahl<br>AFP 3 Larges t Annuity 3 Larges t<br>Herfindahl Ratio Share of 3 Largest<br><!-- End of picture text --> Source : SVS, SAFP

# **2.4 Government Guarantees**

As participation in the pension system is mandatory for all new workers, the state has provided four types of guarantees. The first two apply to the accumulation phase and include a minimum relative return guarantee and a guarantee of coverage against disability and death risks. The minimum relative return guarantee involves the obligation of AFPs to ensure a minimum return relative to the industry’s average. If the AFP cannot honor this obligation with its capital and “encaje<sup>14</sup> ”, it is subjected to supervisory intervention and the government provides the required resources to raise the return to the minimum level. The second guarantee ensures that workers remain properly covered against disability and death risks, in case the insurer defaults in its obligations.<sup>15</sup> The third and fourth guarantees apply to the retirement phase and include a recently introduced solidarity pension pillar, which includes a Basic Solidarity Pension (PBS) and a Pension Solidarity Supplement (APS) and a guarantee against the bankruptcy of annuity providers.

In 2008, the government introduced amendments to the pension system aimed at strengthening the solidarity pillar. Prior to these amendments, the poverty protection system included two programs: a means tested benefit (PASIS) given to poor elderly people who were not receiving any sort of pension; and the minimum pension, offered to pensioners of the private pension funds who fulfilled minimum requirements of eligibility, including a minimum of 20 years of contributions. The government assessed that the then existing structure of PASIS and minimum pension system did not provide incentives for low-income individuals to contribute and the coverage was limited.

> 14 See section 4.2 for a discussion about _encaje_ .

> 15 Since 2009, the insurance of disability and survivorship is provided by a syndicate of insurance companies. All pension fund members are charged the same fee.

8
The perception that the authorities may have attempted to manipulate the indexing mechanism, by depressing the 12-month BOT rate and causing an inverse yield curve to emerge at a time of rising rates, may also have contributed to the crisis.

However, the CCT crisis highlighted the policy dilemma that would arise with excessive reliance on variable rate instruments. A rise in the level of interest rates that could be dictated for monetary policy purposes would have an immediate adverse effect on the interest cost of public debt. Table 2.6 shows the evolution of the interest expense as percentage of GDP, for the past three decades. The ratio of interest expense to GDP doubles in the decade between the mid 1970s and 1980s, and the increase continues until reaching its peak around 12% in 1993. Thereafter, the ratio sees a visible decrease and is nowadays around 5% of GDP.

||**Table 2.6: **|**Interest Cost (**|**% of GDP)**|
|---|---|---|---|
|1970|1.8|1987|8.0|
|1971|2.1|1988|8.2|
|1972|2.4|1989|9.0|
|1973|2.5|1990|9.7|
|1974|2.8|1991|10.1|
|1975|3.7|1992|11.4|
|1976|4.2|1993|12.0|
|1977|4.5|1994|10.9|
|1978|5.1|1995|11.0|
|1979|5.3|1996|10.4|
|1980|5.3|1997|9.0|
|1981|6.2|1998|7.4|
|1982|7.2|1999|6.8|
|1983|7.6|2000|6.5|
|1984|8.2|2001|6.5|
|1985|8.2|2002|5.8|
|1986|8.6|2003|5.3|

Source: Bank of Italy, Italian Treasury, IFS, Salvemini (1992:27), own elaboration.

# **_Distribution Mechanisms, Tax Incentives and Market Structure_**

After the first wave of reforms in 1975, further innovations were introduced in subsequent years. In October 1981, mid-month auctions of Treasury bills were initiated in order to limit the volumes of securities placed, and ease their absorption by the market. In 1984, the “BOT belt” was introduced. This involved a voluntary group of intermediaries that ensured the subscription of a considerable volume of the securities offered during an auction. In exchange, the subscribers received temporary financing from the central bank as a way of anticipating and concentrating demand for funds around the auction dates. This also assisted the central bank in slowly withdrawing from government financing.

For most of this period, the authorities used a combination of issuing techniques. 3- and 6-month BOTs were issued with multiple-price competitive auctions subject to a published minimum issue price, while 12-month BOTs were issued through uniform-price auctions and also subject to a minimum issue price. CCTs and BTPs were offered through public subscription and CTEs through bank syndication and underwriting, usually with predetermined quantities and 16
3 in a certain country and at a certain time and we now turn to a discussion of the relevance to primary commodity expoiter LDC's of the various channels of transmissions mentioned above. What follows is based on earlier work by Lizondo and Montiel (1988).

# 2.2. Effects on A@aregate Demand

Under the assumption that a country is a price taker, the total demand for the primary commodity export produced by the country can be assumed to be unaffected by the devaluation since in most cases the domestic component of that demand can be assumed to be negligible. On the other hand, the relative demand for semitradable and nontradable goods depends on their relative domestic price, and on the elasticity of substitution in consumption. (See, for example, the models by Devarajan et al. (1987, 1993).

A devaluation also affects the demand for domesticallyproduced goods since it produces changes in real income. Lizondo and Montiel (1988) show that the direction of cha-.ige in real income at the initial level of output depends on whether traded goods have a higher share in consumption or in income. The presence of imported inputs make it more likely that the real income effect will be negative but this may not necessarily be so if domestic producers substitute labor for imported inputs (assuming that the real wage did go down). The net effect will depend on the elasticity of substitution in production.

As has been mentioned, a devaluation can also generate a redistribution of income from groups with low marginal propensity to save to groups with high marginal propensity to save, resulting in decline in aggregate demand. However, in his survey of 39 devaluation episodes, Edwards (1989) finds very little evidence of significant changes in income distribution in the period surrounding the devaluations.

Another channel through which devaluation can affect aggregate demand is though the stock of net foreign assets. The overall effect on demand depends upon the composition of the stock and debt financing 2/.

Finally, the net effect of a devaluation on investment is quite complex and, in theory, indeterminate since the various 2/ _An increase in_ the _domestic currency value of foreign assets would be expansionary If foreign assets are repatriated (reVerse capital flight). rhe effect of the public sector external debt will be contractionary (unless the devaluation Is accompanied by compensatory_ debt _relief) only If the increased debt service payments are financed by reduced spending (unless It concerns imports only) or Increased taxatlon._
and China for a time required that a portion of lease sale revenue be dedicated to urban infrastructure construction. Local governments have not applied this rule literally in Ethiopia, and, given the fungibility of budgets, it is impossible to ensure that asset sales are used to fund incremental investment. However, the requirement to enter asset sales as capital revenue in the capital budget can help maintain the policy perspective that one type of asset is being exchanged for another on the municipal balance sheet and that land is not being sold to finance operating expenses.

Paradoxically, the Golden Rule limitation would not assist China in managing the principal fiscal risks that have arisen there from municipal land sales. National authorities fear that municipalities will be _too_ aggressive in using land sales to finance investment, and that excessive investment in urban fixed assets will contribute to overheating the economy. To limit such risks, central government has resorted to more direct restrictions of the kind used to limit or prohibit municipal borrowing. For a six-month period in 2004, municipal land purchases for urban development were halted altogether by central regulation, partly as a fiscal measure to restrain excessive local investment. Central authorities have continued to ban municipalities from acquiring land to create new special economic zones or industrial parks, out of fear that the practice was stimulating inefficient investment and would require massive amounts of infrastructure spending to make the new zones functional.<sup>11</sup>

**Risks of a Real Estate Bubble:** Land prices have the advantage of longterm buoyancy with respect to economic growth and urbanization.  However, they are extremely volatile.  Although at this writing, land prices are rising at a rate of 3040% per annum in India’s large cities; they declined over the period 1998-2002 in response to the Asian financial crisis and other factors. Hong Kong’s experience illustrates the threat to overall fiscal stability that can result from revenue dependence on land sales at a time of decline in the real estate market.

The greatest financial risk manifests itself when land and property values become the primary basis for borrowing. Municipal land is the principal collateral for borrowing by Chinese municipalities’ Urban Development Investment Corporations. China’s banking system, which has concentrated on cleaning up nonperforming loans, many of them to municipal entities or local State-Owned 11 The Vice-Director of the central government Department of Land Use and Management estimated that RMB 200 million (US$25 million) of infrastructure was required to develop each square kilometer of an industrial zone. At that rate, more than RMB 600 billion (US$75 billion) would be required to develop only 10 percent of the undeveloped areas municipalities had claimed for development zones in 2004. In the Vice-Director’s words, municipalities’ excesses implied that “large sums of money will be ‘buried’ in the soil.” (China Daily 2004 c) 19
**Table 7**

**Parameter estimates for region-based yield indices**

||**EMDE**|**LAC**|**SEAO**|**EECA**|**MENA**|**SSA**|
|---|---|---|---|---|---|---|
|**A. Base mode**|**l**||||||
|_Constant_|3526.23<sup>***</sup><br>(34.60)|3383.13<sup>***</sup><br>(201.58)|3359.53<sup>***</sup><br>(42.17)|4097.24<sup>***</sup><br>(183.06)|3138.13<sup>***</sup><br>(67.30)|2807.17<sup>***</sup><br>(43.00)|
|_Trend_|102.05<sup>***</sup>|139.38<sup>***</sup>|131.20<sup>***</sup>|84.97<sup>***</sup>|65.13<sup>***</sup>|35.61<sup>***</sup>|
||(1.43)|(6.00)|(1.36)|(6.43)|(2.36)|(1.08)|
|_PP test_<br>|-4.28<sup>***</sup><br>|-2.85<sup>**</sup>|-3.45<sup>**</sup>|-4.27<sup>***</sup>|-7.77<sup>***</sup>|-5.34<sup>***</sup>|
|_AIC_<br>|796.18<br>|945.92|803.07|977.69|867.87|786.63|
|**B. With**TTT|<sup>2</sup>||||||
|_Constant_|3688.04<sup>***</sup>|4511.85<sup>***</sup>|3420.02<sup>***</sup>|4713.93<sup>***</sup>|3177.91<sup>***</sup>|2886.82<sup>***</sup>|
||(59.54)|(68.38)|(48.75)|(371.94)|(99.75)|(51.63)|
|_Trend_<br>|86.64<sup>***</sup>|31.88<sup>***</sup>|125.44<sup>***</sup>|26.24|61.34<sup>***</sup>|28.02<sup>***</sup>|
||(5.00)|(7.23)|(5.13)|(27.00)|(8.66)|(4.12)|
|TeT<br>2|0.25<sup>***</sup>|1.73<sup>***</sup>|0.09|0.95<sup>**</sup>|0.06|0.12<sup>*</sup>|
||(0.08)|(0.13)|(0.08)|(0.40)|(0.15)|(0.07)|
|_PP test_|-5.01<sup>***</sup>|-8.52<sup>***</sup>|-3.46<sup>**</sup>|-4.92<sup>***</sup>|-7.82<sup>***</sup>|-5.53<sup>***</sup>|
|_AIC_|785.64|856.65|803.64|970.65|869.66|785.33|
|**C. With a stru**|**ctural break i**|**n 1993**|||||
|_Constant_|3640.02<sup>***</sup>|4221.02<sup>***</sup>|3363.30<sup>***</sup>|4571.64<sup>***</sup>|3188.07<sup>***</sup>|2873.56<sup>***</sup>|
||(41.18)|(51.03)|(49.43)|(283.60)|(77.70)|(51.04)|
|_Trend_before_|94.94<sup>***</sup>|87.01<sup>***</sup>|130.96<sup>***</sup>|55.32<sup>***</sup>|62.01<sup>***</sup>|31.46<sup>***</sup>|
||(2.41)|(2.91)|(2.78)|(13.67)|(3.90)|(2.26)|
|_Trend_after_|14.96<sup>***</sup>|110.15<sup>***</sup>|0.50|62.37<sup>**</sup>|6.56|8.73<sup>**</sup>|
||(4.77)|(6.55)|(5.32)|(24.70)|(9.21)|(4.22)|
|_PP test_|-4.93<sup>***</sup>|-9.04<sup>***</sup>|-3.45<sup>**</sup>|-4.95<sup>***</sup>|-7.87<sup>***</sup>|-5.59<sup>***</sup>|
|_AIC_|786.86|853.27|805.06|969.77|869.25|784.37|

**Notes:** Yield is measured as KCal per hectare. Definitions of regional classification can be found in Table 2. Numbers in parenthesis refer to Newey-West standard errors that account for heteroskedasticity and autocorrelation. PP test refers to the Philips-Perron stationarity test, with the null hypothesis that the series under consideration contains a unit root. AIC refers to Akaike Information Criteria. Asterisks denote significance at 10 (<sup>*</sup> ), 5 (<sup>**</sup> ), and 1 (<sup>***</sup> ) percent levels.

_— 24 —_
# **Table 27: Variable descriptions and sources**

|**Variable name**|**Description**|**Source**|
|---|---|---|
|Firm profitability|Operating margin defined as profits before<br>corporate taxes and financial items, measured as<br>a share of turnover.|Statistics Sweden, FEK|
|Treatment (ITT)|Average share of employees 18-25 years old pre-<br>2007 * Reformperiod dummy|Statistics Sweden, RAMS|
|Treatment(Actual)|Share of employees 18-25years old|Statistics Sweden, RAMS|
|Reform Period|Dummy variable signifying reform period<br>(0 ifpre-2007,1 otherwise)|N/A|
|Pre-reformyouth share|Pre-reformyouth share|Statistics Sweden, RAMS|
|Pre-reform firm education level|Average education level of firm employees pre-<br>2007 based on SCB/SUN2000 educational level<br>classification system.|Statistics Sweden,<br>RAMS/UREG|
|Pre-reform firm size|Pre-2007 firm size in terms of number of<br>employees.|Statistics Sweden, RAMS|
|Year Dum.|Time dummies for theyears 2004-2012|N/A|
|Region Dum.|Regional dummies for firm location based on<br>Swedish counties.|Statistics Sweden, FDB|
|Sector Dum.|Sectoral dummies based on SNI2002 sectoral<br>classification system|Statistics Sweden, FDB|

37
water that they did not consume and hence effectively incurring a higher unit charge per cubic meter than larger consumers (Uzin, 1996).

Consequently, in spite of the overall average tariff increase of 20%, the new tariff structure generates lower bills for those consuming less than around 7 cubic meters per month (Figure 4.3). This is close to the average consumption for households in El Alto, but less than a third of the average for households in La Paz.

**Figure 4.3: Changes in tariff structure for water and sewerage**<sup>*****</sup>

<!-- Start of picture text --> 30<br>25<br>20<br>Pre-reform<br>15<br>Post-reform<br>10<br>5<br>0<br>0 10 20 30 40 50 60 70 80<br>Monthly consumption (m3)<br>Monthly bill (US$)<br><!-- End of picture text --> _Source:_ Uzin, 1996 The La Paz peri-urban domestic tariff is taken as an illustration of the pre-reform tariff structure.

Finally, there does not seem to be any evidence that households have had difficulties in paying the post-reform water charges. Indeed, the data show that revenue collection in both La Paz and El Alto improved by around 15% following the reform, and now stands at around 94% in both cities. The percentage of customers disconnected for non-payment has remained stable at around 3.6% in La Paz, and has fallen in El Alto to the much lower rate of 1.5% (Table 4.2).

**<u>Table 4.2: Revenue collection statistics for water and sewerage</u>**

|(%)|La<br>1997|Paz<br>2000|El<br>1997|Alto<br>2000|
|---|---|---|---|---|
|Revenue collection rate (within 6 months)|81.0|94.0|78.0|93.0|
|Percentage of customers disconnected for non-payment|3.5|3.7|2.5|1.5|

_Source_ : AISA, 2000

**Telephones.** The average domestic tariff for fixed telephony doubled from $0.01 to $0.02 per minute. At the same time the tariff structure was changed from a flat rate monthly charge of $3.00 to a fixed charge of either $0.83 or $1.74 (depending on the calling plan), with an entitlement to a block of 100 or 200 minutes per month respectively. Hence, the implicit price per minute in this first block is just under $0.01. However, consumption beyond this attracts a tariff of $0.03 per minute. The implication is that the average COTEL domestic customerwho makes 356 minutes of local calls each monthhas seen bills increase by more than 200% following the reform. However, any customer making less than 242 minutes of local calls each month is better-off under the new tariff structure (Figure 4.4).

23
<!-- Start of picture text --> Investor clout (2)<br>v4 =0<yY/ jyeryye fs<br>H4=0<H) PHoDW |<br>i/a area city<br>y4=yi=0 ye=yi |<br>HA =H) =0 Ho= Hi |<br>° ifa 1<br>Government effectiveness (0)<br><!-- End of picture text -->

<!-- Start of picture text --> Investor clout (2)<br>YavoV vf |<br>H2=-y'+T22Hi f |<br>t/a city<br>yZ =y*s yi<br>HW? = _y' 4.77? HI<br>0 i/a 1<br>Government effectiveness (0)<br><!-- End of picture text -->

<!-- Start of picture text --> Investor clout (12)<br>yo=uy*oyi | 4 / |<br>Ho=T°D HI, Of<br>i/@ city<br>yo=yr>yi<br>Ho =7°? HI |<br>0 i/a 1<br>Government effectiveness (0)<br><!-- End of picture text -->
# **Table S2:** Attrition

||Baseline<br>=1 if|Dropout<br>Completed Hous|Baseline<br>ehold SurveyRou|Schoolgirl<br>nd 4|
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|=1 if Conditional|-0.007|-0.008|0.055***|0.056***|
||(0.031)|(0.029)|(0.019)|(0.018)|
|=1 if Unconditional|||0.058***<br>(0.023)|0.061***<br>(0.021)|
|p-value UCT vs. CCT|-|-|0.896|0.825|
|p-value Treatment|0.828|0.774|0.004|0.002|
|Baseline controls interacted<br>with treatment?|NO|YES|NO|YES|
|p-value on joint F-test for<br>interactions CCT|-|0.009|-|0.332|
|p-value on joint F-test for<br>interactions UCT|-|-|-|0.101|
|p-value UCT interactions vs.<br>CCT interactions|-|-|-|0.690|
|Mean in Control Group|0.843|0.843|0.875|0.875|
|Number of observations|885|885|2,273|2,273|

Notes: Regressions are OLS models with robust standard errors clustered at the EA level. All regressions are weighted to make them representative of the target population in the study EAs. All regressions include baseline centered values of the following variables: age indicators, stratum indicators, household asset index, highest grade attended, an indicator for never had sex. Columns (2) and (4) interact the centered baseline controls with treatment. Parameter estimates statistically different than zero at 99% (***), 95% (**), and 90% (*) confidence.

82