rafmacalaba/datause-encoder-data huggingface dataset:
Appendix B

# **Table B4: Poverty Measures and Inequality based on DHB tables**

|**ESTADO**|**PORC**<br>**PESSO**<br>**INSUF**|**ENTAGE**<br>**AS COM**<br>**ICIENTE**|**M DE**<br>**RENDA**<br>**(P0 )**|**INSU**<br>**M**<br>**RE**|**FICIÊNCI**<br>**ÉDIA DE**<br>**NDA (P1 )**|**A**|**GR**<br>**DESIG**<br>**NA POPU**<br>**RENDA I**|**AU DE**<br>**UALDAD**<br>**LAÇÃO**<br>**NSUFICI**<br>**(P2)**|**E**<br>**COM**<br>**ENTE**|
|---|---|---|---|---|---|---|---|---|---|
||_1970_|_1980_|_1991 _|_1970_|_1980_|_1991 _|_1970_|_1980_|_1991 _|
|Alagoas|88.14|69.59|72.02|0.57|0.36|0.41|0.42|0.22|0.28|
|Bahia|84.95|60.34|71.55|0.54|0.29|0.42|0.39|0.18|0.29|
|Ceará|90.04|70.23|72.78|0.64|0.39|0.43|0.49|0.26|0.30|
|Maranhão|90.06|74.17|79.10|0.55|0.40|0.48|0.38|0.27|0.34|
|Paraíba|91.79|73.10|73.67|0.66|0.41|0.43|0.52|0.28|0.30|
|Pernambuco|84.19|60.02|65.17|0.54|0.30|0.37|0.40|0.18|0.25|
|Piauí|94.50|80.17|78.14|0.69|0.49|0.49|0.54|0.36|0.35|
|**Rio Grande do**<br>**Norte**|**89.98**|**65.97**|**66.87**|**0.63**|**0.35**|**0.38**|**0.49**|**0.23**|**0.26**|
|Sergipe|87.13|62.54|66.52|0.57|0.31|0.36|0.41|0.19|0.24|
|**Brasil**|**67.90**|**39.47**|**45.46**|**0.39**|**0.18**|**0.24**|**0.27**|**0.11**|**0.16**|
|Nordeste|87.85|66.53|71.68|0.58|0.35|0.42|0.43|0.23|0.29|

54
in polity score for those regimes that do not fail over the observation period (those that “survive” through the end of 2003).

**Table 1.   Autocratic Regimes, Type of Transition and Increases in Polity Score**

||Column 1<br>|Column 2<br>|Column<br>|3<br>|
|---|---|---|---|---|
||Autocratic Regimes that<br>Transition to Limited<br>Democracies|Autocratic Regimes that<br>Transition to<br>Autocracies|Autocratic Regi<br>Survive throu<br>End ofthe S|mes that<br>gh the<br>ample|
|Total Observations|65|116|66||
||N<br>%|N<br>%|N|%|
|0 Increases in Polity|41<br>63|93<br>80|25|38|
|1 Increase in Polity|13<br>20|14<br>12|19|29|
|2 Increases in Polity|4<br>6|8<br>7|11|7|
|3 Increases in Polity|5<br>7|1<br>1|7|10|
|4 Increases in Polity|1<br>2|0<br>0|4|6|
|5 Increases in Polity|1<br>2|0<br>0|0|0|
|Mean Age|13.4|10.3|20.8||
|Median Age|10|6|14||

Sources: Regime Dates: Compiled by the Author, see accompanying appendix. Increase in Polity Score: Polity IV An autocracy is defined as a regime that started with a polity score of 2 or less. A democratic regime is one that comes to power with a polity score of 3 or more.

Thirty-seven percent of the autocracies that transition into limited democracies increase polity at least once during their lifetime, whereas only 20% of the regimes that transition to autocratic regimes increase their polity score. For those autocratic regimes that outlive the sample period (column 3), 62% increase polity score at least once.

The data is compelling and motivates the present analysis; however, it is hardly conclusive. In addition to providing the backdrop for the discussion that follows, Table 1 also introduces the endogeneity issues that plague the discussion of democracy and development. It could be that extension of the political franchise reduces political competition and decreases the likelihood of regime ending power struggles; or it could simply be that short-lived autocratic regimes don’t live long enough to extend the franchise, and thus fewer extensions are observed. Similarly, the transitions in Figure 2 could be a manifestation of increasing trends toward democratization (the Third Wave) – if such a trend exists then longer-lived regimes are more likely to fail later in the sample period and are more likely to be replaced by democratic regimes. The direction of causality cannot be inferred from this simple correlation. The model that follows in the next section shows how new constraints on executive authority in the form of an extension of the franchise could result in increased survival of an autocratic regime.

7
# **Tax Compliance Perceptions and Formalization of Small Businesses in South Africa**

Jacqueline Coolidge and Domagoj Ilic*

* J. Coolidge (corresponding author, jcoolidge@worldbank.org) and D. Ilic are consultants with the World Bank

We thank the National Treasury of South Africa and the South Africa Revenue Service for initiating this research. Thanks to the Foreign Investment Advisory Service (FIAS, a multi-donor facility of the World Bank Group), USAID, and the Government of Switzerland for financial support. Thanks to Citizen Survey and Professor Rajen Govender for the survey work and preliminary analysis. Thanks to Richard Bird and Michael Engelschalk for peer review. The opinions expressed here do not necessarily reflect those of the World Bank, its Executive Directors or member countries. All errors are our own.
- 23 -

At first glance, our sample data also seem to support the fact that competitive pressure exists in the road procurement market of Nepal. Although the level of competition is still low, the bids relative to engineering cost estimates tend to decline, as the competition increases (Figure 21). Of course, however, this is merely on a simple correlation basis; the competition effect has to be tested formally by estimating Equation (1).

**Figure 21. Competition and normalized bids**

<!-- Start of picture text --> 2.5<br>ln( bid / cost ) = 1.741 - 0.222 ln( num )<br>R2 = 0.1927<br>2.0<br>1.5<br>1.0<br>0.5<br>0.0<br>0 5 10 15<br>Number of bids<br>Bid / Cost estimate<br><!-- End of picture text --> To capture the impact of security issues, _securitybefore_ is included, which is defined by the number of security-related incidents in a project host district during the three months prior to the auction. Note that this is constructed based on the information of incidents before each auction. This is the best information that potential bidders can know and incorporate in their bid calculation. Based on the past history of security incidents, they are assumed to estimate the likelihood of similar future incidents.

_X_ controls for other contract-specific technical characteristics, such as engineering cost estimates, length of roads, width of the road, thickness of the surface, and used materials (see Table 4 for details).<sup>10</sup> Note that the engineering cost estimate, which is calculated by DDCs prior to public tendering, is included in _X_ to control the observable and unobservable size

> 10 A small but positive value is used to avoid logarithms of zero in independent variables, if they are zero.
Annex VII: Correlation analysis between selected determinants of welfare and poverty across Economic Regions _(P(E,WjRIEG), P(A,WIRI,))_

||_Education_<br>_w_|_and household_<br>_elfare_|_Asset ow_<br>_househ_|_nership and_<br>_old welfare_|
|---|---|---|---|---|
|_Economic Regions_|_PS - 1994_|_PS - 1998_|_PS -1994_|_PS -1998_|
|_Ouest_|.683|.7104|.849|.9053|
||[.204]|[.178]|[.068]*|[.005]*|
|_Sud_|.800|.5138|.7493|.5548|
||[.104]|[.3758]|[.086]**|[.254]|
|_Cent re-Sud_|.789|.8034|.715|.871|
||[.112]|[.1011]|[.175]|[.0108]-|
|_Centre -Nord_|.868|.8025|.5899|.6382|
||[.056]"*|[.1021]|[.217]|[.1727]|
|_Nord_|.935|.8383|.889|.6853|
||[.019]*|[.076]***|[.110]|[.2017]|
|_Ouaga-Bobo_|.813|.8627|.8835|.9669|
||[.095]**F|[.0598]***|[.0083]*|[.0004]*|
|_Autres Villes_|.874|.7748|.9528|.8879|
||[.053]*'|[.1238]|[.0009]*|[.0076]*|
|_Sud-Est_|.817|.6431|.8701|.8595|
||[.091]'*|[.2417]|[.0550]***|[.0131]**|

* Significant at the I percent level.

** Significant at the 5 percent level.

*** Significant at the 10 percent level.

Annex VIII: Rank ordering economic regions on distribution of income and welfare

||_Distribu_|_tion of income_|_Distribu_|_tion of poor_|
|---|---|---|---|---|
|Economic regions||**_U(i)_**|**_U";,_**|**U(i)**|
|Ouest|6|4|6|3|
|Sud|1|1|4|2|
|Centre-Sud|5|6|7|7|
|Centre-Nord|7|5|8|6|
|Nord|2|2|3|1|
|Ouaga-Bobo|4|8|2|4|
|Autre Villes|8|7|1|8|
|Sud-Est|3|3|5|5|

27
<!-- Start of picture text --> o& India:Son2° preference<br>o O ~<br>a<br>co<br>3.<br>5°<br>2<br>By<br>50<br>§<br>{i 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995<br>Year of birth<br>+——+ Quintile2 +—— Quintile 3<br>-— Quintile4 +——— Quintile 5<br>Generated by regressing son preference on wealth, urban, higher education and interactions<br>with year-of-birth and state fixed effects. Standard errors clustered by state.<br><!-- End of picture text --> <!-- Start of picture text --> 8o Bangladesh:Son preference<br>i<br>a<br>5<br>a<br>3<br>BN<br>a'<br>5<br>5<br>ii 61940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995<br>Year of birth<br>+—— Quintile2 —— Quintile 3<br>+—— Quintile4 '——— Quintile 5<br>Generated by regressing son preference on wealth, urban, higher education and interactions<br>with year-of-birth and state fixed effects. Standard errors clustered by state.<br><!-- End of picture text --> <!-- Start of picture text --> Nepal:Son preference<br>OL<br>cae<br>a<br>co<br>8<br>6<br>&*<br>g<br>oN<br>a!<br>G<br>§<br>ti 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995<br>Year of birth<br>— Quintile2 '—— Quintile 3<br>-—— Quintile4 +——— Quintile5<br>Generated by regressing son preference on wealth, urban, higher education and interactions<br>with year-of-birth and state fixed effects. Standard errors clustered by state.<br><!-- End of picture text --> <!-- Start of picture text --> 8 Pakistan:Son preference<br>oT<br>go<br>a<br>co<br>8<br>6<br>50<br>2<br>Ba<br>a<br>G<br>§<br>i 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995<br>Year of birth<br>*— Quintile2 +—— Quintile 3<br>+—— Quintile4 +——— Quintile 5<br>Generated by regressing son preference on wealth, urban, higher education and interactions<br>with year-of-birth and state fixed effects. Standard errors clustered by state.<br><!-- End of picture text -->
<!-- Start of picture text --> 100%<br>4<br>=<br>oO<br>E 80%<br>&<br>&<br>°<br>2 60%<br>a}<br>2<br>ast<br>= 40%<br>So<br>2<br>S<br>20%<br>2<br>Lae<br>=<br>val<br>0<br>1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010<br><!-- End of picture text --> (IMF and World Bank Group («Other multilateral creditors HEE Bilateral creditors
The United Kingdom adopted a flexible e-invoice system in accordance with the EU Directive on e-invoicing. According to the UK’s VAT Notice on electronic invoicing, e-invoices can be issued where invoice authenticity and integrity is ensured through such means as an advanced electronic signature, an EDI, or business controls enabling a reliable audit trail between an invoice and the supply of goods or services.<sup>25</sup> Therefore, businesses can use such systems as “security of networks/communication links,” “access controls,” and “message transfer protocols” to the extent that the taxpayer can secure the authenticity and integrity of invoice data. In addition, a wide range of electronic message formats including a structured XML format, an unstructured PDF format, and traditional EDI standards are allowed as a valid e-invoice. In 2012, 55 percent of invoices in the UK were in PDF format, a relatively easy approach to e-invoicing (Institute of Financial Operations, 2012, p. 8). Taxpayers may also choose to outsource electronic invoice to a third party but they continue to assume the legal responsibilities and liabilities for the contents, storage, and production of the invoices. According to the Eurostat, 11 percent of enterprises with at least 10 employees in the UK sent or received e-invoices in 2010.<sup>26</sup>

# Non-EU Countries

# _Chile_

Under a strict invoice control system that Chile had maintained since 1954, invoices had to be stamped by the Chilean tax authority prior to use as they functioned as a proof of transaction and evidence for claiming input VAT credit to tax authority. Such strict rules made Chile pioneer e-invoicing in Latin America in 2003 that enabled the tax authority to seal invoices electronically and significantly accelerate invoice processing. The introduction of e-invoice in Chile removed the limitations of the traditional invoice administration and greatly simplified tax procedures (Piaggesi, Sund, & Castelnovo, 2011, p. 385). In 2005, the Chilean tax authority launched e- invoice portal, through which 200,000 small businesses could electronically issue and receive invoices (Toro, 2005). In September 2013, the tax authority announced that electronic invoice would become mandatory for large enterprises earning more than 100,000 (UF) annually effective from November 2014 and that it expected all companies to make the transition to the new system by 2018.

# _Mexico_

Since 2011, Mexico has made it compulsory for companies with an annual income of MXN4 million (approximately USD320,000) to issue e-invoice. Beginning on January 1, 2014, the e-invoice requirement covered entities with annual receipts of MXN250,000 (approximately USD20,000). The primary objective of the mandatory

> 25 VAT Notice 700/63: Electronic Invoicing;

> 26 http://epp.eurostat.ec.europa.eu/tgm/table.do?tab=table&init=1&plugin=1&language=en&pcode=tin00114;

14
# Table 6

Decomposition of the difference in hourly wages between public and private sector (robustness) PANEL A – GROUP DIFFERENCES IN THE PREDICTORS WEIGHTED BY GROUP SIZES

||||Overall difference<br> <br>|||
|---|---|---|---|---|---|
||Charac<br>|teristic|Estimate<br>S.E.<br>0.587<br>***<br>(0.125)<br>s effect<br>Coeff<br> <br>|icients|effect<br>|
||Estimate||S.E.<br>Estimate||S.E.|
|_Aggregate Effect_|0.612|***|(0.217)<br>-0.025||(0.261)|
|_Aggregate effect without constants_|||0.158||(0.373)|
|_Labor market characteristics_|-0.287|***|(0.050)<br>0.204|***|(0.051)|
|_Socio-demographic characteristics_|0.001||(0.025)<br>-0.025||(0.325)|
|_Education_|0.296|***|(0.038)<br>-0.014||(0.025)|
|_Industry_|0.535|***|(0.204)<br>0.066||(0.203)|
|_Location_|0.068|***|(0.018)<br>-0.065|**|(0.027)|
|Constant|||-0.183||(0.398)|

PANEL B – SELECTION CORRECTION FOLLOWING DUBIN AND MCFADDEN (1984)

||||Overall difference<br> <br>||
|---|---|---|---|---|
||Charac<br>|teristic|Estimate<br>S.E.<br>0.505<br>***<br>(0.097)<br>s effect<br>Coefficien<br> <br>|ts effect<br>|
||Estimate||S.E.<br>Estimate|S.E.|
|_Aggregate Effect_|0.580|***|(0.208)<br>-0.075|(0.234)|
|_Aggregate effect without constants_|||0.349|(0.348)|
|_Labor market characteristics_|-0.213|**|(0.108)<br>0.125<br>**|<br>(0.054)|
|_Socio-demographic characteristics_|-0.061|***|(0.021)<br>0.220|(0.351)|
|_Education_|0.327|***|(0.032)<br>-0.065|(0.042)|
|_Industry_|0.493|***|(0.179)<br>0.104|(0.124)|
|_Location_|0.034|***|(0.013)<br>-0.035|(0.023)|
|Constant|||-0.424|(0.410)|

## PANEL C – TRIMMED SAMPLE

||||Overall difference<br> <br>|||
|---|---|---|---|---|---|
||||Estimate<br>S.E.<br> <br> <br>|||
||Charact<br>|eristic<br>|0.677<br>***<br>(0.128)<br>s effect<br>Coeff<br> <br>|icient|s effect<br>|
||Estimate||S.E.<br>Estimate||S.E.|
|_Aggregate Effect_|0.474|**|(0.217)<br>0.203||(0.265)|
|_Aggregate effect without constants_|||0.187||(0.283)|
|_Labor market characteristics_|-0.224|**|(0.113)<br>0.117|**|(0.052)|
|_Socio-demographic characteristics_|-0.069|***|(0.020)<br>0.079||(0.275)|
|_Education_|0.304|***|(0.028)<br>-0.059|*|(0.033)|
|_Industry_|0.455|**|(0.197)<br>0.070||(0.117)|
|_Location_|0.008||(0.012)<br>-0.019||(0.022)|
|Constant|||0.016||(0.367)|

_Notes_ . (1) The symbols *, ** and *** indicate significance at the 10%, 5% and 1% levels, respectively. (2) Weights have been used for the decomposition. (3) The reported standard errors are bootstrap standard errors from 200 replications. (4) Detailed variables and correction terms are not depicted.

As mentioned in Section 3, the benchmark selection-corrected Oaxaca type decomposition uses the average coefficients of public and private sector workers. This follows a suggestion by

- 26 -
# **Returns to Education in Azerbaijan**

# **Some New Estimates**<sup>**1**</sup>

Vicente Garcia Moreno Harry Anthony Patrinos JEL Codes: I21, I26, J23, J24, J31 Keywords: Education, Returns to Education, Azerbaijan

> 1 The views expressed here are those of the authors and should not be attributed to the World Bank Group. Thank you to Elvira Anadolu and Sabina Guliyeva for helping access official cost data, and thanks to Naveed Naqvi, Katia Marina Herrera Sosa, Lire Ersado, Nina Arnhold, Alexandria Valerio, Flora Kelmendi and Igor Kheyfets for motivation and providing access to studies. I also thank George Psacharopoulos, Eduardo Velez and Chris Sakellariou for comments.
productivity growth. The rest of the paper will look at these issues and constraints and suggests a future strategy for the agriculture sector.

# IL Issues **of Resource Use. Depletion, and Devellpment**

Much of the increased agricultural output has been due to an expansion in land area cropped and liberal availability of water, but future growth cannot rely on increasing supplies of cultivable land and irrigation. Part of the past output increases have come at the expense of depletion of the resource base. Management of water resources is poor, and damage to soil resources considerable. The land available for cropping is being reduced due to waterlogging and salinity, resulting from drainage problems associated with the expansion of irrigation, and policies such as under pricing of irrigation water. Soil erosion is a serious problem. Reliance on a minimal nunber of crop rotations had led to a decline in soil fertility. These problems are not an inevitable consequence of agricultural growth. A different pattern of agricultural growth - a pattern that emphasized natural resource investments - would have done a better job of preserving the natural resource base. This section shows how natural resources have been mismanaged and how investments in physical and human capital have not taken the right form.

## Land

This sub-section describes Pakistan's soil resources and associated problems. Charts 3 and 4 show the long-term trends in total, irrigated, and rainfed area, and irrigated area by method (canal or tubewell).

Chart 3

### Cultivated Area

<!-- Start of picture text --> 25<br>20<br>Mllion 1 5<br>Nec'tar.: I 0<br>5<br>56 58 60 62 64 66 63 70 72 74 76 73 S0 32 14 36 SS 90 92<br>Flscal Year<br>*Total Area U irrigated * R ain fed l<br><!-- End of picture text --> Source: Statistical Survey of Pakistan 9
<!-- Start of picture text --> il<br>ll<br>ll<br>30000 :<br>|<br>o|<br>o |<br>© |<br>ra |<br>Q 20000 |<br>3 |<br>o |<br>ro |<br>E |<br>2 10000<br>0<br>0 2 4 6 8 1<br>CRI<br>—-- MeanCRI -—~-—- Median CRI<br><!-- End of picture text -->
||_ei_ = 1_._25<br>_λ_ down|_−_1.07|5.71|_−_4.65|—|—|—|2.11|15.68|2.48|_−_36.31|_−_33.46|_−_25.53|_−_32.15|_−_4.96|5.31|_−_0.34|_−_0.01|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||_em_ = 1_._5|0.27|_−_1.82|1.56|—|—|—|_−_0.85|_−_4.95|0.20|31.61|17.90|23.92|18.52|_−_0.17|0.15|0.01|0.01|
|se|_φ_=_._1|0.00|0.00|0.00|—|—|—|0.00|0.00|0.00|0.00|0.00|0.00|0.00|_−_6.64|0.00|0.00|0.00|
|chmark ca|_ξ_ = 0_._84|0.28|_−_0.99|0.71|—|—|—|_−_0.68|_−_4.54|_−_0.92|24.70|16.72|20.79|17.14|_−_0.21|0.19|0.04|_−_0.02|
|the ben|_λt_ up|_−_0.57|3.93|_−_3.36|—|—|—|_−_0.59|_−_4.15|_−_0.87|23.86|2.86|38.02|7.65|_−_7.70|5.22|2.55|_−_0.07|
|respect to|_foit_ fxed|0.14|0.65|_−_0.78|0.937|0.856|0.945|_−_1.22|_−_10.69|_−_3.00|15.58|11.73|17.46|14.75|_−_2.96|1.71|_−_0.23|1.48|
|ed values with|_Gt_ fxed in<br>fxed costs|0.03|0.11|_−_0.134|1.000|0.998|0.999|0.02|2.36|_−_0.19|_−_2.30|_−_0.43|_−_1.77|_−_0.50|0.20|_−_0.28|0.04|0.05|
|n predict|_Igt_ = 0|0.19|_−_2.42|2.22|0.862|0.544|0.828|2.661|21.8|3.31|_−_42.98|_−_23.92|_−_45.05|_−_26.63|8.76|_−_7.14|_−_1.75|0.13|
|ferences i|_Gt_ fxed|0.15|_−_1.74|1.59|0.917|0.720|0.896|1.60|12.66|2.01|_−_32.31|_−_17.26|_−_34.08|_−_19.40|6.04|_−_4.74|_−_1.39|0.09|
|Table 7: Di|Variable|GVA share of agriculture (%)|GVA share of manufacturing (%)|GVA share of services (%)|GVA share of agriculture, _R_2|GVA share of manufacturing, _R_2|GVA share of services, _R_2|Ave. no. of workers in agriculture|Ave. no. of workers in manufacturing|Ave. no. of workers in services|GDP percentage change|Agricultural output % change|Manufacturing output % change|Services output percentage change|Private consumption share (%)|Private investment share (%)|Public investment share (%)|Fixed-costs share (%)|

52
- 20 -

Of particular note, there is a general alleged notion that public procurement might be affected by corruption and collusion. Auriol (2006) estimates the cost of corruption to be between 4 and 10 percent of procurement spending. Under the circumstances where an auctioneer can design an award mechanism in the presence of a threat of corruption, it can be shown, unsparingly, that in small markets, sole sourcing would be optimal, whereas for large purchases, competitive bidding is the best choice. The government is assumed to buy a fixed amount of public services from a private firm through a delegate, i.e., public procurement authority. It is also assumed that the procurement authority can meet with one firm to sidecontract on its posterior choice of procurement method. Then, there are two forms of corruption. While “capture” occurs when a firm takes the initiative of bribing the government official to obtain an advantage, “extortion” happens when the official demands a bribe from a firm under the threat of excluding it from the procurement process, bribe which is referred to as facilitation payments. Since fighting extortion entails costs and yields no benefit, the optimal delegation scheme does not prevent it. To cope with the effects of capture, on the other hand, public purchasers should receive incentive payments to resist capture, and those payments should increase with the size of the purchase.<sup>13</sup> One of the important factors in the recent electricity sector reform in Andhra Pradesh, India is that the state government reinforced the anticorruption mechanism within the utilities (Bhatia and Gulati, 2004). A survey of corruption in South Asia conducted by Transparency International indicates that petty corruption is endemic in utilities (Table 6) (Word Bank, 2009). Utility officials may be faced with a lot of opportunities to accept bribes from procurement to linesmen, and the bidding and evaluation process is one of the most controversial and thus potentially corruption-prone areas (Table 7). Moreover, even if procurement is successfully implemented, public utility officials can be a significant deterrent factor of the sector reform, as experienced in India. Without proper incentive and accountability mechanisms, unions of low-level employees may refuse to refuse to materialize important investments, such as meter installation (Gulati and Rao, 2007).

13 In practical terms, this should be implemented in tandem with improvements in public sector productivity. Otherwise, it would run the risk of the government’s losing fiscal discipline.