rafmacalaba/datause-encoder-data huggingface dataset:
# Figure 9: Real Consequences in the U.S. of Clinton Deficit Reduction Prograrm and Maastricht Agreement

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**Table 7: Descriptive statistics by period**

|**Stt**|**O**|**utputs (x100**<br>|**0)**<br>||**Inputs**||
|---|---|---|---|---|---|---|
|**a.**|**Passenger**|**Tons of**<br>**freight**|**Aircraft**<br>**movements**|**Employees**|**Runways**|**Boarding**<br>**bridges**|
|||**1996-1999 (**|**7 airports, 26**|**observations)**|||
|**Mean**|5,039.7|145.4|119.1|723.5|1.5|9.7|
|**STD**|4,586.1|125.7|80.9|690.0|0.5|10.1|
|**Min.**|250.6|21.4|30.5|77.0|1.0|0.0|
|**Max.**|14,705.1|409.2|293.8|2,056.0|2.0|38.0|
||**2**|**000-2003 (1**|**7 airports, 60**|**observations)**|||
|**Mean**|6,136.6|132.8|112.4|429.3|1.5|11.8|
|**STD**|5,314.4|124.2|88.0|465.8|0.5|10.9|
|**Min.**|654.8|10.4|29.5|56.0|1.0|0.0|
|**Max.**|21,694.0|418.9|334.5|1,940.0|2.0|38.0|
||<br>**2**|**004-2007 (2**|**2 airports, 85**|<br>**observations)**|||
|**Mean**|6,579.4|121.1|99.1|433.9|1.5|12.0|
|**STD**|5,992.7|120.6|83.6|421.9|0.5|10.7|
|**Min.**|157.9|0.0|1.9|20.0|1.0|0.0|
|**Max.**|25,882.0|470.9|379.0|1,598.0|2.0|56.0|

In Table 8 we present the main results: TFPC by sub period and by airport. In order to avoid potential biases due to unbalanced panel data, Malmquist index computations were performed separately for each two-year sequential period using in each case a balanced panel of airlines.

Average productivity growth oscillated over the three sub periods. Between 1995 and 1999, airports in the region posted an average annual productivity growth of -2.7%. However, it should be noted that limited data is available for this period and consequently the result is biased by the high negative value of the airport in Barranquilla, Colombia. Airports in Brazil show an increase, on average of 5.4%. Average productivity growth during the intermediate period (19992003) was negative (-1.2% per year), and was driven mainly by some airports which experimented dramatic losses in productivity, like EZE (Aeropuerto Internacional Ministro Pistarini, Buenos Aires) which showed an average loss in productivity of -18.1% per year over this period as a direct consequence of the severe economic and financial crisis Argentina suffered during 2001/2002. On the contrary, positive rates of growth appear to be the norm (with only some exceptions) during the last sub period (2003 to 2007). The average TFPC rate was 3.9% during this period, with many airports experimenting annual productivity growth rates close to, or even higher than, 10%.

19
of MWRs, while in Denmark and Sweden the calculation was impeded by the lack of data on ex ante and ex post bonus payments. Without detailed data on bonus payments, the calculation of MWRs, based only on minimum guaranteed benefits, would have been meaningless.

The calculated MWRs are very high in both Chile and Switzerland. Joint life indexed annuities in Chile had a MWR of 1.078 in March 2004 when discounted by the government bond yield curve and based on cohort annuitant tables. However, this fell to 0.892 when corporate bond rates were used (Rocha and Thorburn 2007:172).

In Switzerland, the MWR for joint life nominal annuities of the second pillar amounted to 1.152 in 2004 when discounted by the government bond yield curve. The very high MWR reflects the use of a fixed annuity conversion factor of 7.2 percent at a time of very low interest rates. In 2000, when interest rates were much higher, the MWR stood at 1.025 (the five-year bond rate equaled 3.80 percent in 2000 against 2.36 percent in 2004).

**<u>Table 11: Money's Worth Ratios</u>**

|Country|Joint Life Annuities<br>Cohort Annuitant Tables<br>Government Bond Rates|Joint Life Annuities<br>Cohort Annuitant Tables<br>Corporate Bond Rates|
|---|---|---|
|Indexed|||
|Chile 2004|1.078|0.892|
|UK|0.880||
|Nominal|||
|Switzerland 2004|1.152||
|Switzerland 2000|1.025||
|Switzerland*|0.985|0.875|
|UK*|0.987|0.873|
|US*|0.929|0.841|
|Canada*|0.980|0.868|

* See Rocha and Thorburn (2007:173) for details. Source: Buetler and Ruesch (2007) and Rocha and Thorburn (2007).

The MWRs in Chile and Switzerland compare favorably with those prevailing in other countries and indicate that they may not be sustainable in the longer run (Table 11). Switzerland has already decided to lower gradually the uniform annuity conversion factor in its second pillar, while use of improved mortality data and greater appreciation of the long-term risks of annuities may contribute to a lowering of MWRs in Chile.

# **4. Provider Regulation**

The regulation of providers of retirement products covers both the providers of annuities (which are usually life insurance companies) and the providers of phased withdrawals (which are usually the pension institutions that handle the accumulation accounts). The regulatory framework includes the institutional structure of the market, the regulation of investments, and capital regulations. The latter relate to the valuation of assets, the measurement of liabilities and the application of risk-based capital rules. Investment and capital regulations aim to ensure the solvency of annuity providers and play a crucial part 30
**_Table 4_** _Capital and maintenance costs of reaching a given RAI objective_

|**Country**|**RAI objective**<br>**(percent)**|**Total cost of upgrading Tertiary**<br>**Roads (percent of current GDP)**|**Total annual maintenance costs (paved**<br>**roads) (percent of GDP)**|
|---|---|---|---|
|Sierra Leone|51|30|1.1|
||70|85|1.8|
|Togo|56|25|2|
||69|65|2.2|
|Burkina Faso|24|16|1.7|
||32|42|2.1|
|Guinea|40|17|1.1|
||47|39|1.4|

Given that goals and costs are so country-dependent that it is impossible to cost overall rural access, we can reverse the question and ask: How much access could countries achieve by 2030 if they each spent 1 percent of their GDP on new rural roads every year? Our results show that with optimistic assumptions on GDP growth, the increase in access could go from 9 percentage points on average in East Asia to 18 percentage points on average in Sub-Saharan Africa (Table 5). Table 5 also shows that most of the gains can be obtained by spending only 0.5 percent of GDP every year, since the cost of incrementally improving access quickly escalates as the served population increases.

**_Table 5_** _Universal access to paved roads is not within countries’ reach by 2030._

||**Share of rura**<br>**Current RAI**|**l population within 2km of a primary**<br>**RAI if all countries spend 0.5**<br>**percent of their GDP per year to**<br>**2030**|**or secondary road (percent)**<br>**RAI if all countries spend 1**<br>**percent of their GDP per**<br>**year to 2030**|
|---|---|---|---|
|East Asia & Pacific|52|59|61|
|Europe & Central Asia|29|37|40|
|Latin America & Caribbean|34|42|45|
|Middle East & North Africa|39|49|51|
|South Asia|43|54|57|
|Sub-Saharan Africa|29|42|46|

Note: GDPs for each country grows according to the Shared Socio-Economic Pathway 5, which has the highest growth rate (Dellink et al., 2017).

# **3.3. Environmental impact of rural roads**

A growing body of literature is sounding the alarm on the potential negative impacts of opening or upgrading roads on forest cover and biodiversity, although the degree of impact strongly depends on the local context and road type. (Asher et al., 2018) do not find a significant impact of rural roads on forests in India, while (Pfaff et al., 2018) and (Damania et al., 2018) find that impacts can be significant in the Amazon rainforest and in Africa.

To understand the possible order of magnitude of the impact, we run three scenarios: (i) newly paved rural roads lead to deforestation in an area of 25 meters on each side of the road (minimum impact, mainly due to road works), (ii) the impact spreads to 2 kilometers on each side of the road; and (iii) the impact extends to 10 kilometers on each side of the road (this is not the most extreme scenario we could consider, since Desbureaux and Damania (forthcoming) find that in Kenya the blast of a road on biodiversity can go as far as 25km). If the impact is 2km or more of deforestation, as Figure 6 shows, the consequences for 11
**Figure 9:  Uncertain Delivery Times and Revenue**

<!-- Start of picture text --> 60<br>Market price ($)<br>50<br>40<br>30<br>20<br>10<br>0<br>1 2 3 4 5 6 7 8 9<br>Source: Authors.<br><!-- End of picture text --> <!-- Start of picture text --> Time (days)<br><!-- End of picture text --> Uncertainty in demand forecasts also leads to uncertainty in expected revenues due to the direct relation between revenue and sales. With expected values of the demand distribution being lower than the corresponding deterministic demand because of uncertainty, revenues are, in general, lower if there is some risk of errors in forecasts.

Risks attached to any attribute (maritime transit time, dwell time, total sales) of the profit function lead to probabilistic formulations that generally have an adverse impact on absolute profit levels but do not change the strategies of market players. In a comfortable price-setting scenario, experience suggests that market players tend to be overcautious and to ―build delay time into their production planning‖ to prepare for the worst situation. If the container happens to arrive on time, they just delay the shipment until they need it (Wood et al. 2002, 169). This hedging behavior is therefore another justification of why ―shippers are biased in favor of utilizing the port facility as much as possible‖ (UNCTAD 1985).

# **3. An Empirical Analysis of Demand: Lack of Competence or Purpose?**

A key factor is the lack of competence and professionalism of small importers and customs brokers, who often do not exercise due diligence in the clearance process. This results in considerable delays in payment and slows down the entire logistics chain. The capacity and professionalism of the private sector have a large effect on the clearing process, even greater than expected. For instance, an analysis of Douala port by a major freight forwarder found that customs procedures cause only one percent of very long—20 days or more—cargo delays. The same analysis calculated that lack of or erroneous documentation by the importer or delays by the pre-inspection company are far more time-consuming than customs procedures.

# **Findings from firms’ surveys**

By using data from firm surveys launched in five SSA countries - Kenya, Nigeria, South Africa, Uganda, Zambia we attempt, through statistical analysis, to validate some of the theoretical assumptions presented in the previous section. The main objective of the analysis of firm surveys is to 20
5 share in total world exports of ma-nu`ctures.s Specifically, if xij is the value of country i's exports of j and Xit is the country's total exports of manufactures, its revealed comparative advantage index is, where the w subscripts refer to world trade totals. The RCA index may take values from zero to infinity with those above unity indicating the country has a comparative advantage in the product. A point of considerable interest would be to determine how the above "revealed" comparative advantage index, for (say) all, or groups of, developing countries c3mpares with the NBER labor-intensity index for a common group of products. A high correlation (i.e., high developing country RCAs for industries with high labor-intensity ratios) would be an important verification of the Heckscher-Ohlin theory.

Before *ndertaking such an empirical test, howaver, it is useful to consider factors that might cause the Balassa and NationaL Bureau indices to differ. First, protectionism in major markets could limit developing countries' exports of a labor-intensive product to a sufficient extent that the RCA index is constrained below levels (above unity) that it would reach in the absence of trade barriers. Such a situation might, for example, occur for (say) textile 5 Foods and agricultural raw materials have generally been excluded from revealed comparative advantage computations since it is felt that protectionism and subsidization in these sectors distorts trade to an extent that comparative advantage cannot be measured using the Balassa approach. Following standard practice, this study employs a definition of manufactures that includes all items classified in SITC 5 through 8 less 68 (nonferrous metals) Dlus a few processed food and raw material products items classified in other groups. The latter were added to achieve consistency with the definition used and results presented in the NBER study.
community leaders. These factors are of course not independent of the degree of devolution itself, and for this reason the implementation of devolution is more likely to be successful if it is approached as a gradual process rather than an instant policy change.

It is no accident that some of the most successful examples of decentralization are to be found in the U.S., with its long commitment to the devolution of authority for education and training to the community. Its responsibility for funding most of its expenditure on education and training through propercy taxes has both encouraged the development of local managerial expertise and has provided it with the necessary operational resources, with the result that one can even cite instances of thriving d.-ecentralized systems based on foroal education establishments, for example, the Oregon training system based on community colleges.

However one can also point to promising examples of decentralization in developing countries. For example, the Middle East survey reports significant movements in this direction in Jordan, Egypt and Morocco.

# 9.3 The need for information

The need for an appreciation of comparative experience Although the importance of a knowledge of relevant international comparative experience for policy formulation is obvious, it has been ignored in the past and is still not always given due respect. There continues to be ample evidence of policymakers in some countries subscribing to imperatives based on little more than their intuition. And since policymakers in national planning units often have little direct, detailed knowledge of training and employment, their intuition is often poorly developed.

The two most prevalent biases are an overestimation of the proportion of the labor force that requires significant occupational training and over-reliance on institution-based training, particularly school-based training.

The unreceptiveness of policymakers to the notion that employers can make a major contribution to skill development is exemplified by the Conference of African States on the Development of Education in Africa hosted. by Unesco in Addis Ababa in 1961. Ignoring a background paper by an acknowledged expert which drew attention to the fact that "many categories of skills are best developed on the job and/or through apprenticeship arrangements. In most countries, all semi-skilled labor and most highlyskilled craftsmen and lower level supervisors can be trained on the job" (Harbison, 1961), the Outline of a Plan for African Educational Development produced by the conference, which in most other respects faithfully incorporated Harbison's recommendations, asserted a supposed need for a greater emphasis on school-based training: "... at the second level, increased emphasis should be placed on technical education and on agricultural education. Trained manpower in these two areas is essential to the economic development of African States." (Unesco, 1961b, p. 11). The effect was to

- 104 -
E = P (2) where P ii ii<sup>∗E</sup> ii<sup>∗EELLPP</sup> ii<sup>PP</sup> government from project , and is the government’s loss given distress from project . ii<sup>is the probability of distress for projectii,E</sup> ii<sup>is the exposure at distress of thePP</sup> The P ii ii EELLPP ii using a flexible parametric survival model of the realization of distress conditional on projectii<sup>, E</sup> ii<sup>and EELLPP</sup> ii<sup>are obtained separately. The probability of distress of a PPP is predicted</sup> specific and country-specific institutional variables and macroeconomic shocks. The<sup>PP</sup> E is estimated based on the debt and equity invested in the project. The is determined based on ii PP different practices by countries in case of termination of PPP contracts and the recovery rates of ii defaulted loans to infrastructure projects. EELLPP

# **4.1. Probability of distress**

# **_4.1.1. Econometric model_**

The probability of distress of a PPP at a specific point during its contract period is predicted by estimating a flexible parametric proportional hazards model (Royston and Parmar 2002; Royston and Lambert 2011).<sup>11</sup> The model is an extension of the parametric proportional hazards model with a Weibull baseline hazard function. The generalization allows for a non-monotonic baseline hazard function using restricted cubic splines. Accordingly, coefficients of the following equation are estimated to maximize the likelihood of the observed distribution of failure times: 2 i 0 + p p p i ,i i i i i ,m m (3) mm mm ii,p mmp mmp ln HH(tt|XX ) = γγ �γγ zz (ln tt) + XX ββ + XX ββ + XX ββ where i ) is the log cumulative hazard at time mm=1 for project _i_ conditional on i = p i ,i i i ,m �. p is the vector of project-specific time-invariant covariates, ln HH(tt|XX tt XX i ,i i is the vector of country-specific time-varying institutional covariates and i ,m is the ii,p mmp ii,p �XX , XX , XX XX vector of country-specific time-varying macroeconomic shocks. The terms under the summation mmp operator represent the set of restricted cubic spline terms in log time scale, XX . The time scale XX is chosen as the percentage of contract period elapsed. mm zz (ln tt) The probability of distress, P 0<sup>and tt, given that the project survives until tt</sup> 0<sup>can</sup> be recovered using the log cumulative hazard from equation (3), and the relationship between the ii<sup>, between time tt</sup> survival function, and the cumulative hazard function (see appendix A for detailed discussion). The estimated probability of distress can be written as follows: SS(tt), P 0) (4) ii ii<sup>�</sup> = 1 −SŜ (tt|tt

> 11 The model is estimated in Stata using the stpm2 routine, which has been authored by Lambert and Royston (2009).

11
accounts, whom cashed their checks instead of depositing them in a bank account. Using subsidies, banks were encouraged to open bank accounts and recipients were encouraged to switch to electronic payments. The Treasury offered to pay banks $12.60 for each ETA account they established for benefit recipients, and the Treasury specified a minimum set of characteristics that these accounts must meet (the accounts could not cost account owners more than $3 a month and they could not levy a fee for electronic deposits coming in). The switch would benefit the government as supplier (lower costs), but in the end could also help the recipient by giving him access to financial services. In the end, the take-up was less than expected, suggesting again that lack of access to financial services is part of a broader issue of social exclusion. Similar experiences exist with encouraging taxes payments and returns to be made electronically, where the usage is often concentrated among those already having access and otherwise better off.

Besides these methods, there are other options open for governments to stimulate access for households to banking and other basic financial services. For one, the regulatory system can be used to direct, although not mandate banks to address the problem. This is what might be described as the Community Reinvestment Act (RCA) model used in the US. Second, authorities can mandate all banks to provide minimum banking services (“basic accounts”) for otherwise excluded segments of the market. Third, governments can rely on banks with a social commitment (in the legal form of either public banks, cooperatives, foundations, the postal network or proximity banks such as local savings banks) offering very restricted retail services. Each of these approaches has its advantages and disadvantages.<sup>6</sup> The US Community Reinvestment Act (CRA) enacted by the US Congress in 1977 and revised in 1995 aims to improve financial access. It aims to help meet the credit requirements of the communities in which banks operate, including low to moderate income neighborhoods. Each bank is rated every three years as to the bank’s performance in making loans to low- and moderate-income people (rather than for its process for complying with CRA), allowing the general public to apply pressures for non-

> 6 The following sections draw extensively on Peachy and Roe, 2004.

26
illustrates that sale of a few well chosen and located parcels can generate more than a year’s worth of capital spending, and dwarf the value of municipal bond issues.

**Table 4.1: Selected Recent Transactions Using Land Assets Selected Developing Countries**

|**Location/Activity**|**Land Financing Amount/**<br>**Use of Proceeds**|**Comparative Magnitude**|
|---|---|---|
|**Cairo, Egypt:**Auction of<br>desert land for NewTowns<br>(May 2007, 2100 hectares).|US$3.12 billion: to be used to<br>reimburse costs of internal<br>infrastructure and build<br>connecting highway to Cairo<br>RingRoad|117 times total urban property<br>tax collections in country;<br>equal to 10% of national<br>government revenue|
|**Cairo, Egypt:**Private<br>installation of “public”<br>infrastructure in return for<br>developable land (2005-<br>present).|US$1.45 billion of private<br>infrastructure investment, plus<br>7% of serviced land turned<br>over to government for<br>moderate-income housing.|Will provide range of urban<br>infrastructure services for<br>more than 3,300 hectares of<br>newly developed land, without<br>financial cost to government.|
|**Mumbai, India:**Auction of<br>financial center land (Jan.<br>2006, Nov. 2007, total 13<br>hectares) by Mumbai<br>Metropolitan Regional<br>Development Authority<br>(MMRDA).|US$1.2 billion: to be used<br>primarily to finance projects<br>in<br>Metropolitan<br>Transportation Plan.|10 times MMRDA’s total<br>capital spending in fiscal<br>2005; 3.5 times total value of<br>municipal bonds issued by all<br>urban local bodies and local<br>utilities in India in past<br>decade.|
|**Istanbul, Turkey**: Sale of old<br>municipal bus station and<br>former brewery. (March &<br>April, 2007)|US $1.5 billion, auction<br>proceeds, to be dedicated to<br>capital investment budgets.|Total municipal capital<br>spending in FY2005 was<br>US$994 million. Municipal<br>borrowing for infrastructure<br>investment in 2005 was<br>US$97million.|
|**Cape Town, South Africa:**<br>Sale of Victoria & Albert<br>Waterfront property by<br>Transnet. (Nov. 2006)|US$1.0 billion, to be used to<br>re-capitalize Transnet and<br>support its investment in core<br>transportation infrastructure.|Sale proceeds exceeded<br>Transnet’s total capital<br>spending in FY 2006; equal to<br>17% of 5-year capital<br>investment plan prepared in<br>2006.|
|**Bogota, Colombia:**<br>_Contribucion de Valorizacion,_<br>betterment fees,|US $1.0 billion collected<br>1997-2007; US $1.1 billion<br>planned for 2008-2015. Used<br>to finance city street and<br>bridge improvement program.|Finances 50% of street and<br>bridge improvements. Other<br>sources of financing: US$50<br>million IFC loan; US$300<br>million international, peso-<br>linked bondissue.|

Source: Reproduced from Peterson (2009:3) Peterson (2009) documents a range of different types of land-based transactions in a variety of developing countries that have reaped very rich fiscal rewards. (See Table 4.1.) These range from outright sales or leases to developers’ exactions, betterment levies, and land pooling. These tools are particularly useful in 28