rafmacalaba/datause-encoder-data huggingface dataset:
56 TABLE 27 AVERAGE LABOR PRODUCTIVITY IN THE PUBLIC SECTOR

|O S|YEAR|TLPU|TCXPU|LPPU|
|---|---|---|---|---|
|I<br>|1975<br>|246168<br>|806263171<br>|3265.97<br>|
|2<br>|1976<br>|269021<br>|639421594<br>|3239.41<br>|
|3<br>|1977<br>|286591<br>|953290667<br>|3326.31<br>|
|4<br>|1978<br>|288009<br>|S15432078<br>|2831.27<br>|
|5<br>|1979<br>|292560<br>|657611067<br>|2247.78<br>|
|6<br>|1980<br>|288481<br>|698769801<br>|2422 24<br>|
|7<br>|1961<br>|271335<br>|1040691031<br>|3835 45<br>|
|*<br>|1942<br>|265737<br>|1159383623<br>|4475.79<br>|
|9<br>|1963<br>|278421<br>|1145813425<br>|4115.40<br>|
|10<br>|1934<br>|278685<br>|1183203087<br>|4263.61<br>|
|I1|1985|275539|1235489774|4483.90|

TABLE 28 AVERAGE LABOR PROOUCTIVITY IN THE PRIVATE SECTOR

|36S|YEAR|TLPR|TCXPR|LPPR|
|---|---|---|---|---|
|1<br>|1975<br>|455503|1349899510|2963.52|
|2<br>|1976<br>|474455<br>|1460154619<br>|3077.60|
|3<br>|1977<br>|469443<br>|1565849653<br>|3335.51|
|4<br>|1971<br>|51S504|1729528029|3348.53|
|5<br>|1979<br>|503203<br>|1417109671<br>|2616.18<br>|
|6<br>|19s0<br>|51615?<br>|1264006543<br>|2448.88<br>|
|7|1931<br>|534305<br>|1605024269<br>|3003.95<br>|
|a<br>|1962<br>|567044<br>|1814106721<br>|3199.23|
|*<br>|1933<br>|534967<br>|1956178301|3344.08|
|10<br>|1984<br>|611833<br>|2203699624|3601.77|
|il|1935|632031|2439497483|3659.47|

TLPUUTOTAL NMSER Of EWPLOVIES IN THE PUBLIC SECTOR **TCAFUaTOTAL** VALUE OF RIAL OUTPUT INt THE PUSk SECTOR IOOOTL **LPPUwAVERAGE** OUTPUT PER EWNLOVEEI IN THE PUS SECTORt IOOOTL TLPUOT@TAL **NJEIt** OF E"PLOEEIS IN THE PRIVATE SECTO4 TCXMoTOtAL VALUE Of REAL OUTPUt IN THt PRIV SECTOR IOOTL LFP EAVIEM OUTPUT PER EMPLOYEE IN THE PRIV SECTOR IOOOTL
|**Table 10: Type of remarriage for**|**divorcees by oth**|**er union characteristi**|**cs**|
|---|---|---|---|
||Has a civil<br>contract|Lives with in-laws|Lives with<br>children from<br>previous union|
|Dissolution before age 40|0.025<br>(0.102)|0.156<br>(0.115)|0.215*<br>(0.111)|
|Last dissolution: rural resident|-0.197***<br>(0.060)|0.138***<br>(0.053)|-0.282***<br>(0.065)|
|No children born in last union|-0.072<br>(0.066)|0.103**<br>(0.044)|.<br>.|
|Had a son at time of divorce|-0.105*<br>(0.062)|-0.045<br>(0.069)|0.203***<br>(0.077)|
|Number of marital dissolutions|-0.094|-0.063|0.057|
||(0.089)|(0.062)|(0.074)|
|Ever been to a French school|0.119**<br>(0.052)|0.021<br>(0.053)|-0.125<br>(0.081)|
|Mean of dep. Var|0.18|0.13|0.55|
|N|227|227|177|
|Pseudo R2|0.171|0.129|0.119|

Note: Logit model, marginal effects shown.<sup>***</sup> _p_ < 0.01,<sup>**</sup> _p_ < 0.05,<sup>*</sup> _p_ < 0.1,<sup>+</sup> _p_ < 0.12. Source: Authors’ estimations using PSF1.

41
- Finally, in 2003 and early 2004, the authorities issued one-year fixed-rate special savings certificates as a means of developing retail demand for government securities but public response was limited and their use was also discontinued.

These modest attempts at cultivating strong demand from retail investors contrasted sharply with the determined approach of the early 1990s. To a large extent, they reflected the availability of strong wholesale demand from international investors, which probably resulted in issuing public debt at a lower total cost.

Issuing strategy emphasized the prolongation of the average maturity of public debt and the development of liquid benchmark issues. The latter increasingly focused on 5-, 10- and 20year bonds, gradually replacing intermediate maturities. The frequency of auctions was substantially reduced with a corresponding increase in auction size, while the syndication method was used for new issues of 10- and 20-year bonds. Reopening of past issues to take advantage of favorable conditions in the secondary market was actively pursued. Reverse auctions for specific pre-announced older issues as well as buy-backs and exchanges of issues were organized at regular intervals. These operations aimed at refinancing debt with lower cost and reducing interest payments. Foreign currency and interest rate swaps were also utilized.

|**Table 3.8: Alloc**|**ation of New Issu**|**es by Country**|**and Type of In**|**vestors**|
|---|---|---|---|---|
|(percent of total)|2003 5yrs|2003 10 yrs|2004 5yrs|2004 10yrs|
||4/2008|5/2013|3.5% 4/2009|5/2014|
|Greece|35.6|23.7|22.2|25.0|
|Other Europe|59.3|68.3|70.0|68.8|
|North America|3.2|3.1|2.0|1.0|
|Asia|2.0|3.1|5.3|5.1|
|Other|0.0|1.8|0.4|0.1|
|Total|100.0|100.0|100.0|100.0|
|Banks|20.3|16.3|38.7|34.0|
|Central Banks|4.5|2.4|14.4|33.3|
|Fund Managers|55.1|78.9*|25.9|4.1|
|Hedge Funds|0.0|2.3|7.5|8.2|
|Pension Funds|12.7|0.0|6.6|12.5|
|Insurance Companies|5.8|0.0|5.9|6.9|
|Other|1.6|0.1|0.9|1.0|
|Total|100.0|100.0|100.0|100.0|

* Includes pension funds and insurance companies. Source: Public Debt Management Agency

The strong interest of foreign institutional investors is shown by data on the allocation of new issues. Despite the establishment of a central securities depository and automated trading system since 1995, available data do not allow a complete analysis of public debt holdings by type of investor. This is mainly because data are recorded in nominee accounts. Plans are under way to require banks to indicate the ultimate beneficiaries of nominee accounts, at least for statistical purposes. Data from the Public Debt Management Agency show that foreign institutional investors from other European countries play a major part in subscribing to new 35
levels. In what follows, the data are taken to be monthly. Refer to the price observation in month _m_ of year _y_ as _pmy_ or as _pt_ depending on the context, _t_ = 12( _y_ − _y_ 0 ) + _m_ , where _y_ 0 is the initial year of the sample. Unconditional seasonal factors result either from averaging prices over months or by 1 _n_ regressing on a set of dummy variables.<sup>11</sup> Averaging, one obtains _sm_ = ∑( _pym_ − _~~p~~_ ) where _n y_ =1 unconditional seasonal gap is then just: _gap_ = max( _sm_ ) − min( _sm_ ) .<sup>12</sup> Food price and expenditure data typically trend and this is true of the data analyzed here. The trend may reflect cyclical or secular changes in production or consumption or may result from inflation. Deflation of food prices to obtain real prices is dangerous if food comprises a large proportion of the consumption basket and may distort or eliminate the seasonal features of the data which are of interest. Therefore, nominal (local currency) prices are used here. In a sample covering only a small number of years, any trend in prices will be positively correlated with the seasonal dummy variables—a positive trend will be positively correlated with the dummies for later months and negatively correlated with the earlier dummies. Failure to control for the trend will result in omitted variable bias in the seasonal components. It is therefore desirable to control for the trend in estimating the seasonal components. Even in a longer sample, where the omitted variable bias will be negligible, controlling for the trend will give more precise seasonality estimates.

Detrending involves an implicit or explicit trend model. There is a danger that the choice of model may affect the resulting seasonality estimates. To minimize the judgmental element in this process, a very general estimation model is proposed:

> 11 The same estimates are obtained by regression of the demeaned vector _p_ on the eleven seasonal dummies (but no intercept). Suppose the twelfth dummy is omitted and write the coefficients of the dummy variables as

1 11 the vector _b_ . The _m_ th centered seasonal component is then _sm_ = _bm_ − ∑ _bj_ where _b_ 12 = 0. 12 _j_ =1 12 An alternative approach would be to calculate gaps for each year and average these. The annual gaps calculated in this way are intra-annual ranges. They tend to be an order larger than seasonal gaps since irregular movements can result in the highest or lowest prices in a year occurring at times other than the immediate pre- and post-harvest months.

8
country with a population of approximately 25 million people. Soon after gaining independence from Portugal in 1975 the county descended into a civil war that lasted from 1977 to 1992. By the end of the civil war, Mozambique was one of the poorest countries in the world. As of the early 1990s, Mozambique embraced a new constitution enshrining a market oriented economy and a multiparty political system with free elections. By 2010 the country was one of the fastest growing economies of the world, though GNI per capita was still just US$460.<sup>2</sup> Among the list of countries surveyed by the United Nations Development Program’s Human Development Report of 2013, Mozambique had the third lowest Human Development Index in the World, only higher than Niger and the Democratic Republic of the Congo. Poverty levels in rural areas are particularly severe, with over 57% of the population living below the official poverty line. At the same time, Mozambique has made substantial progress in expanding primary education, with net primary school enrollment rates increasing from 45% in 1998 to 95.5% by 2010. Yet children tend to enroll in school past the appropriate age, and many times struggle with the new social and academic environment, resulting in increased repetition and low academic performance.

The Southern part of the country, including the Gaza province where this study was conducted, had higher incomes and better human development outcomes compared to other provinces in the central and northern areas of Mozambique. However, the province was also one of the most severely affected by the country’s civil war. Partially due to high migration rates of adult males for employment in the mining sector, the province had the highest rate of young adults living with HIV-AIDS (Crush et al, 2010). One-quarter of the Gaza population aged 15 to 49 was HIV positive, while the national rate was estimated to be around 11% (Instituto Nacional de Saúde et al. 2010). Women were more severely hit by the HIV epidemic, with a prevalence rate of 30% in Gaza province.

While population based child development indicators in Mozambique are scarce, the 2011 Demographic and Health Survey (DHS) reported child growth in terms of height and weight.<sup>3</sup> Nationally, 42.6% of children under age five were stunted, 14.9% were underweight and 5.9% were wasted. The conditions in Gaza province were relatively better off, with 26.8%, 6.3% and

> 2 GDP growth has averaged around 7% per year in the period 2005-2015

> (http://data.worldbank.org/country/mozambique).

> 3 The positive association between children’s linear growth and cognitive development is well documented (Sudfeld et al, 2015).

5
Table 2: Descriptive statistics - individual level variables

||Algeria|Ghana|Morocco|Nigeria|Full sample|
|---|---|---|---|---|---|
|Tax morale|7.12|9.35|9.49|8.76|8.74|
||(3.19)|(1.35)|(1.37)|(1.74)|(2.15)|
|Trust in the neighbourhood|2.70|2.48|2.99|2.91|2.76|
||(1.00)|(0.83)|(0.84)|(0.84)|(0.90)|
|Trust in public institutions|2.29|2.70|2.55|2.39|2.50|
||(0.84)|(0.67)|(0.86)|(0.66)|(0.76)|
|Age|38|30|37|31|34|
||(15.10)|(12.70)|(13.57)|(11.69)|(13.51)|
|Male|0.51|0.50|0.50|0.50|0.50|
||(0.50)|(0.50)|(0.50)|(0.50)|(0.50)|
|A religious person|0.84|0.97|0.89|0.96|0.93|
||(0.36)|(0.16)|(0.31)|(0.20)|(0.26)|
|Self employed|0.09|0.34|0.37|0.41|0.31|
||(0.29)|(0.47)|(0.48)|(0.49)|(0.46)|
|Education|4.60|4.33|2.67|5.19|4.30|
||(2.74)|(2.20)|(2.46)|(2.18)|(2.54)|
|Married|0.47|0.42|0.54|0.48|0.47|
||(0.50)|(0.50)|(0.50)|(0.50)|(0.50)|
|Financial satisfaction|5.99|4.91|5.57|5.64|5.50|
||(2.46)|(2.55)|(2.40)|(2.35)|(2.47)|
|Redistribution|5.57|4.86|7.96|5.18|5.67|
||(3.27)|(2.99)|(2.49)|(3.04)|(3.18)|
|Human right|2.70|3.16|2.32|2.63|2.73|
||(0.90)|(0.81)|(0.88)|(0.97)|(0.94)|
|Political position|6.03|5.54|5.51|5.59|5.62|
||(2.12)|(2.72)|(2.35)|(2.44)|(2.51)|
|Observations|1200|1552|1200|1759|5711|

Notes. Standard deviations in parenthesis.

# **3.3 Econometric issues**

As emphasized above, both dimensions of trust are expected to be positively correlated with tax morale. Although this is consistent with the predictions of the theoretical model, it is evident that tax morale and trust are entangled, making it challenging to identify the causal effects of trust on tax morale. Potential endogeneity issues might arise from reverse causality and error measurement issues. Respondents might be reluctant to reveal their attitude toward taxes truthfully as it might appear socially undesirable or as a form of social opposition toward state policies (Tripp, 1997; Kinsey, 1991). To identify the causal effect of 18
Policy Research Working Paper 4997

# **Abstract**

Some researchers have documented that the path of development is remarkably related to the pattern of sectoral diversification. Others have highlighted the relation between productive specialization and economic progress. This paper explores the role of product market competition and intellectual property rights protection in the pattern of sectoral diversification. The paper confirms the insight of the innovation literature, that competition induces firms to specialize and upgrade the quality of existing goods. However, it reveals a new force, called the imitation effect, through which competition biases technical change toward product diversification. The paper shows that if knowledge spillovers increase with imitation, or the degree of product substitution is high, weak protection of property rights encourages firms to create low-quality goods, thereby directing technical change toward diversification. The predictions are tested with data on Italian firms' innovation activity. They are found to be consistent with observed behavior.

This paper—a product of the Trade and Integration Team, Development Research Group—is part of a larger effort in the department to understand key links between competition, intellectual property rights protection and the pattern of sectoral diversification. The research was funded by the Bank Executed Child Trust Fund No.TF093822 for TRTARESEARCH ON TECHNOLOGY, TRADE & INTELLECTUAL PROPERTY RIGHTS, under Sub Fund TF080297. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at acusolito@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
**Figure 11: Top Five Constraints of Rural Market Towns and Their Rural Area Ratings, 2005**

**Figure 12: Top Five Constraints of Rural Areas and Their Rural Market Town Ratings, 2005**

<!-- Start of picture text --> 70% 70%<br>60% 65% 56% 61% Rural Area Rural Town 60% 65% 56% 61% Rural Area Rural Town<br>50% 50%<br>39%<br>40% 40%<br>35% 34% 35% 34%<br>30% 28% 30% 28%<br>25% 23% 23% 25%<br>20% 18% 19% 20% 18%<br>10% 10%<br>0% 0%<br>Finance Utilities Governance Marketing Taxation Finance Utilities Transport Marketing Governance<br>Rural town rank 1st 2nd 3rd 4th 5th Rural area rank 1st 2nd 3rd 4th 5th<br>Rural area rank 1st 2nd 5th 4th 8th Rural town rank 1st 2nd 6th 4th 3rd<br>Percentage of firms citing constraints as major or severe Percentage of firms citing constraint as major or severe<br><!-- End of picture text --> Source: 2005 Tanzania RICS The claim that limited access to public utilities is the second most important constraint is difficult to interpret because 57% of rural entrepreneurs are traders who may not need electricity or water access for their rural businesses, but instead may reflect their household’s desire for better access to services. Factors that constrain enterprise productivity and growth differ by geographic zone. Figure 13 plots the top five business constraints identified by rural entrepreneurs - finance, public utilities, transport, marketing, and governance. Several findings emerge from the visualization.

Finance, utilities, and transport infrastructure clearly emerge as the main factors that impede business operations and growth, but there are large regional differences. Financing constraints are perceived as particularly severe in the Lake region, Northern Highlands and Southern zones. Access to public utilities and transport infrastructure is perceived as a major and severe constraint in the Western zone. Finally, the map clearly indicates that Central Tanzania is the only zone that scores better in three aspects of the rural investment climate (finance, transport infrastructure, and governance). With the exception of rural finance, it is rarely the region with the lowest level of business constraints. However, it is the only zone that scores relatively better in all of these areas.

21
Policy ReseaRch WoRking PaPeR 4496

# **Abstract**

Subnational insolvency is a reoccurring event in development, as demonstrated by historical and modern episodes of subnational defaults in both developed and developing countries. Insolvency procedures become more important as countries decentralize expenditure, taxation, and borrowing, and broaden subnational credit markets. As the first cross-country survey of procedures to resolve subnational financial distress, this paper has particular relevance for decentralizing countries. The authors explain central features and variations of subnational insolvency mechanisms across countries.

They identify judicial, administrative, and hybrid procedures, and show how entry point and political factors drive their design. Like private insolvency law, subnational insolvency procedures predictably allocate default risk, while providing breathing space for orderly debt restructuring and fiscal adjustment. Policymakers’ desire to mitigate the tension between creditor rights and the need to maintain essential public services, to strengthen ex ante fiscal rules, and to harden subnational budget constraints are motivations specific to the public sector.

This paper—a product of the Economic Policy and Debt Department, Poverty Reduction and Economic Management Network—is part of a larger effort in the network to strengthen the Bank's capacity to analyze subnational fiscal reforms and challenges. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at lliu@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
4

-

-

**TABLE** 5.1 **A**

**CONTROL-GROUP ESTIMATES OF THE PROGRAM EFFECTSV/ (ratios at** current prices)

|Perlcds<br>CrDmpared|Change in<br>GDP Growth|Change ir.<br>Investment/CDP|Change in<br>Saving/GDP|Change in<br>Exports/GDP|
|---|---|---|---|---|
|1985-88<br>with<br>1970-80|0.017<br>(2.402)|-0.015<br>(-1.108)|0.014<br>(0.839)|0.042<br>(2.023)|
|i985-88<br>with<br>1981-84|0.028<br>(3.141)|0.017<br>(1.498)|0.021<br>(1.438)|0.042<br>(3.070)|

a/ As measured by the coefficient of the program dummy, 0,, of equation (2). The t-values are in parentheses.

**TABLE 5.1 B CONTROL-GROUP ESTIMATES OF THE PROGRAM EFFECTS/ (ratios at constant prices)**

|Periods<br>Compared|Change in<br>**GDP**Growth|Change in<br>Investment/GDP|Change in<br>**Saving/GDP**|Change in<br>**Exports/GDP**|
|---|---|---|---|---|
|1985-88<br>with<br>1970-80|0.017<br>(2.402)|-0.031<br>(-1.786)|-0.013<br>(-0.620)|0.038<br>(1.603)|
|1935-88<br>with<br>1981-84|0.028<br>(3.141)|0.017<br>(1.322)|0.025<br>(1.516)|0.018<br>(1.466)|

a/ As measured by the coefficient of the program dummy, 6,, of equation (2). The t-values are in parentheses.
**Exhibit 2.11 – Profitability indicators** _Medians_ _<u>and means for 2003-07</u>_

||**Real sales**<br>**growth(%)**|**Op. profit**<br>**margin(%)**|**ROA(%)**|**ROE(%)**|**Real asset**<br>**growth(%)**|
|---|---|---|---|---|---|
|**Second Tier**||||||
|Median|3.4|9.9|6.4|12.6|-1.3|
|Mean|7.5|17.2|8.0|15.1|3.6|
|**Top Tier**||||||
|Median|7.0|15.0|9.3|19.2|0.0|
|Mean|13.8|18.9|10.1|19.9|5.0|
|**Peer group (WS)**||||||
|Median|6.0|9.3|5.2|7.7|0.9|
|Mean|9.1|12.3|4.4|5.3|6.5|
|**LMI countries, excl. Egypt (WS)**||||||
|Median|3.0|8.8|4.3|5.7|-4.2|
|Mean|5.6|12.6|3.9|4.3|0.2|

_Source: Coface Egypt;Worldscope; World Bank staff analysis_ As regards industry differences, Exhibit 2.12 shows that in all sector performance indicators have been growing strongly over the period 2003-07, with the exception of the ROE and sales growth of Top Tier Consumer Staples firms, which confirms earlier findings. Both in Construction and Materials and industrial Cyclical, Top Tier firms outperform Second Tier firms unambiguously. However, in Travel and Leisure, Second Tier firms seem to outperform Top Tier firms in terms of margins and ROA. However, Top Tier firms have been showing superior growth rates, indicating that they are catching up rapidly.

After taking into account factors that can bias the results, we confirm that the median Top Tier firm shows significant outperformance. In doing so, we conduct a median regression analysis to assert that the findings not simply reflect sectors differences between Top and Second Tier firms or the economic cycle. The first two columns of Exhibit 2.12 nonetheless clearly show that Top Tier firms show superior results in terms of margins, ROA, and ROE. Top Tier firms outperform Second Tier firms by 4.9 pp, 3.7 pp, 5.3 pp, respectively. Still, there is no longer a significant difference in sales growth. These findings are very similar to the earlier simple median analysis. However, because Top Tier firms are 6 to 7 times larger, the last two columns of Exhibit 2.13 also take into account whether a company is small, medium, or large. However, even after this correction, Top Tier firms show higher profitability, implying that firm size does not fully account for the difference between the tiers.

12