rafmacalaba/datause-encoder-data huggingface dataset:
The government’s unwillingness or inability to prevent income inequality from increasing signals a clear risk of rising social discontent. In common with leaders in many other countries, China’s leadership is concerned with its own political survival. Specifically, in recent years, China’s leaders have expressed their concern about the possibility of “social instability,” which can impede China’s continued rapid growth (Knight and Ding 2012: 295–306). One potential source of social instability is income inequality.

We have seen that the increase in China’s income inequality takes three main forms: among households, across regions, and between rural and urban areas. However, comparisons in these dimensions of inequality at the national level may not be important. Because of the narrowness of people’s reference groups, it may be more important for a government concerned about social instability to remedy the causes of income inequality at the local level. However, extra-local orbits of comparison are widening owing to the increasing use of the Internet and the growth of “the greatest migration in human history.” The analysis of rural-urban migrants living in households showed that this group had the lowest mean happiness—owing to the transfer of their reference group to the city, with its higher incomes, and the unequal treatment of rural _hukou_ households in matters of employment, residence, education, and other services (Knight and Gunatilaka 2011). A qualification is in order: unhappiness does not necessarily translate into social discontent. This relationship might depend on the extent to which people perceive their unhappiness to be manmade and capable of being remedied by the government.

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# **Table 4.1: Impact of WTO Accession in 55,098 Household Model on Economy-Wide Variables in Russia --** Policy Results and Decomposition of Effects

(results are percentage change from initial equilibrium)

||Bench-<br>mark|<br>WTO<br>accession|<br>WTO<br>accession<br>(equal Ruble<br>transfers)|<br>Improved<br>market<br>access<br>only|Tariff<br>reform<br>only|Reform of<br>FDI<br>barriers<br>only|CRTS<br>Model|WTO<br>Accession<br>with partial<br>reform of<br>FDI barriers|
|---|---|---|---|---|---|---|---|---|
|||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|**Aggregate welfare**|||||||||
|Mean welfare (EV as % of<br>consumption)||7.3|7.2|0.7|1.3|5.3|1.2|4.1|
|Standard deviation of EV as % of<br>Consumption<sup>_a/_</sup>||_(2.2)_|_(2.2)_|_(0.5)_|_(0.8)_|_(1.5)_|_(0.7)_|(1.3)|
|Welfare (EV as % of GDP)||3.4|3.4|0.3|0.6|2.4|0.6|1.9|
|**Government budget**|||||||||
|Tariff revenue (% of GDP)|1.4|0.9|0.9|1.4|0.8|1.4|0.9|0.8|
|Tariff revenue (% change)||-33.2|-33.2|8.7|-38.3|10.9|-43.5|-35.2|
|**Aggregate trade**|||||||||
|Real exchange rate (% change)||2.6|2.6|-0.5|2.0|1.1|0.3|1.8|
|Aggregate exports (% change)||14.4|14.4|2.3|8.1|3.7|5.9|11.9|
|**Returns to mobile factors**|||||||||
|Unskilled Labor (% change)||3.7|3.7|0.1|0.6|2.9|1.0|1.7|
|Skilled Labor (% change)||5.3|5.3|0.7|1.7|2.8|1.9|3.2|
|Capital (% change)||1.8|1.8|-0.6|1.0|1.4|0.9|2.2|
|**Percent of Factors that must adjust**|||||||||
|Unskilled labor||1.2|1.2|0.3|1.2|0.4|0.8|1.3|
|Skilled labor||1.4|1.4|0.5|0.6|0.7|0.6|1.0|
|Capital||0.5|0.5|0.1|0.3|0.1|0.3|0.4|

* Source: Authors' estimates

a/ Numbers The means and standard deviations are the population weighted means and standard deviations of the 55.098 estimates..

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* 13 -

## CANADA

Canadian ODA increased from S1.631 billion in 1985 to SI.885 billion in 1987. Continued growth is anticipated with the government's decision to maintain appropriations at the 0.5 percent of **GNP** through 1991.

Detailed computerized project information was provided for 1985 to 1988, with the caveat that such data do not identify Safe Motherhood components. The distribution given below was estimated using the Herz-Measham criteria.

For comparability with othe; data sets in this review, funds for water supply systems have been excluded unless water and sanitation are integral parts of assistance to other general health systems. The Canadian data offers the potential for attributing at least a third of such services to SM, since access to water is directly relevant ;o the daily work of women of reproductive age and contributes to the reduction of anemia-producing parasitic diseases.

# Policy

Canada intends to focus on maternal health and family planning, with the broader goal of improving the health of women. This intent suggests a willingness to identify more specific statistical marbzers f3r maternal health.

An important component of Canadian assistance is the value given to country demand; financing depends less on preplanning by CIDA than on responding to requests from cooperating countries.

|Estimated|Financial Flows<br>S mill|to Developi<br>ions|ne Countrie|s|
|---|---|---|---|---|
||1985|1986|1987|1988|
|Total Health Sector<br>(bilateral, multilateral<br>nongovernmental)|77.6|101.58|131.56|148.1|
|Health plus Water/Sanitation|149.0|172.0|223.9|327.8|
|Safe Motherhood (SM)|15.7|36.6|43.0|44.1|
|SM with Water/Sanitation|51.3|72.2|89.6|133.9|

Canadian International Development Agency 200, Promenade du Portage Hull (Quebec) Canada KlA OCG4
hit only the tradable sector of an economy directly, whereas the non-tradable sector might be affected only indirectly. Countries with large non-tradable sectors will therefore be relatively less affected by fluctuations in terms of trade. We partly control for this by including the ratio of trade to GDP in our estimation below. The interaction between financial intermediary development and inflation volatility can be interpreted as coming from either variable, since both are subject to policy decisions, at least to a certain extenm.. Further, inflation volatility might reflect not only monetary policy volatility, but other factors as well, such as demand shocks and business cycle effects.

# **3. Data and Econometrics**

## **_3.1. The Data_**

The data come primarily from published World Bank and IMF sources.'<sup>8</sup> We create three panel data sets by aggregating over different time periods on data from 1960 to 1997. This serves partly as a robustness check on the results, and partly to avoid the problems caused by aggregating on unusual initial- or end-years. Our constructed data sets are a three-period panel (aggregated over the periods 1960-72, 1973-85, and 198697), a four-period panel (1960-69, 1970-78, 1979-87, 1988-97), and a six-period panel (1960-66, 1967-72, 1973-78, 1979-84, 1985-90, 1991-97). We maintain a consistent sample of 63 countries across all data sets, but the number of observations differs by aggregation.'<sup>9</sup> We will focus the discussion here and in the empirical results on the threeperiod panel, since it provides the most efficient estimates of standard deviations (i.e. based on the largest number of observations). Table I describes the data and Table 2 presents correlations.

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countries still exhibit high levels of product market regulation that stifle competition, growth, and innovation in the services sector (OECD, 2005). Moreover, there is still significant cross-country heterogeneity in the degree of liberalization and the quality of the regulatory framework facing the services sector, which may help explain the differences in performance documented in Section 3.

**_Figure 13: Average KLEMS Labor Productivity Growth and Skills in Services Sub-Sectors_**

<!-- Start of picture text --> EU-8 Countries Average<br>8%<br>6%<br>4%<br>2%<br>0%<br>Low Skill Intensity High Skill Intensity<br>1997-2000 2000-2004<br>Czech Republic Estonia Hungary<br>12% 15% 10%<br>8%<br>10%<br>6%<br>8% 10%<br>4%<br>6% 2%<br>4% 5% 0%<br>2% -2% Low Skill Intensity High Skill Intensity<br>0% 0% -4%<br>Low Skill Intensity High Skill Intensity Low Skill Intensity High Skill Intensity -6%<br>1997-2000 2000-2004 1997-2000 2000-2004 1997-2000 2000-2004<br>Latvia Lithuania Poland<br>10% 10% 10%<br>8%<br>8% 8%<br>6%<br>4% 6% 6%<br>2% 4% 4%<br>0%<br>-2% Low Skill Intensity High Skill Intensity 2% 2%<br>-4% 0% Low Skill Intensity High Skill Intensity 0%<br>-6% -2% Low Skill Intensity High Skill Intensity<br>1997-2000 2000-2004 1997-2000 2000-2004 1997-2000 2000-2004<br>Slovak Republic Slovenia<br>10% 6%<br>5%<br>4%<br>0%<br>Low Skill Intensity High Skill Intensity<br>-5% 2%<br>-10%<br>0%<br>-15% Low Skill Intensity High Skill Intensity<br>1997-2000 2000-2004 1997-2000 2000-2004<br><!-- End of picture text --> Source: KLEMS database 2007.

Note: For each country and skills-related category, a simple average is taken across all sub-sectors in that category of their geometric averages of labor productivity growth in 1997-2000 and 2000-2004.

To capture the extent of services liberalization across ECA countries, we use the European Bank for Reconstruction and Development (EBRD) index of progress in policy 29
**Decoupling and recoupling**

depending on the specific issue at hand, stock holdings, capital flows or both may prove informative.

In addition, the investor behind a particular flow may also be relevant to understand FG. For example, a passive buy and hold portfolio investor may behave closer to real investors (FDI), with limited turnover (flows) for a given holding. By contrast, institutional or professional investors would tend to be more sensitive to expected return differentials, with both a larger turnover and a bigger impact in terms of price action its correlation across markets and with respect to economic fundamentals. Global mutual funds are a case in point in this regard. While, as a subset of cross-border holdings, they are generally a poorer proxy than other more comprehensive measures, they may shed some additional light on the role of the international investor as a financial transmission channel. To the extent that these funds tend to keep close to their benchmarks, they may introduce an additional source of market co-movement, particularly in the event of sharp swings in global risk aversion (when contributions and redemptions lead to purchases and sales in all markets at the same time).

In this light, we try to analyze different measures of de facto FG by their advantages and disadvantages of using them as proxies of financial globalization in emerging markets. More precisely, we look at two different sources: (i) US Treasury’s TIC monthly survey data on the market value of sales and purchases, and stocks holdings of foreign securities by US-domiciled investors (by the market where the security is issued); and (ii) EPFR’s monthly data on global fund flows and assets under management (AUM) (by the issuing country).

In our study, we are interested in asset prices on a monthly basis, and to address whether financial recoupling (or greater financial contagion) in the late 2000s was associated with financial globalization. At first sight, frequency and length problems arise with both Lane and Milesi-Ferretti’s (2007) and BoP statistics. Annual foreign stocks from LMF are available until 2007, and are inadequate to analyze asset prices and financial globalization in the late 2000s, particularly at times when the global financial crisis may have significantly modified gross foreign asset positions. On the other hand, while updated BoP statistics are available, they are usually reported on a quarterly or an annual basis. To study whether greater flow intensity generates the monthly asset correlation behind financial recoupling, we need higher frequency data such as the U.S. Treasury’s TIC and EPFR data.

<u>12</u>
the system? How reliable is transaction processing, and what are the consequences for the integrity of FMIS reporting?

4.5 **Involve sector experts and economists in the dialogue.** Given that FMIS data form the backbone for government financial reporting, confidence in FMIS data is paramount. Since economists and sector experts draw on FMIS reports to inform analytical work and the policy dialogue, it is important to involve them in the conversation, such that they are cognizant of the implications of FMIS deficiencies on their work.

4.6 **Technological change presents opportunities and risks.** Technological change presents a host of opportunities that may challenge a traditional approach to budget management. Innovations in the ICT sector are happening at a rapid pace and hold promise in strengthening accountability, transparency, and efficiency throughout the budget cycle. While it will be important to stay abreast new developments, it is equally important to caution against security risks and leaping forward without having adequate analog complements in place. The policy and institutional environment will remain paramount in determining the systems’ effectiveness in supporting budget management. Setting up an FMIS system may be a necessary prerequisite for effective budget management, but it is not sufficient.

**58**
impacts appear to occur in districts that tend to have higher overall performance before the new school grants program is introduced.<sup>17</sup>

# **Table 6. Impact of performance-based grant on eligible primary and junior secondary** **<u>schools in Jakarta</u>**

||Govern|ment v. non-g<br>Jaka|overnment sch<br>rta<br>Ji|ools in<br>d|
|---|---|---|---|---|
||Primary<br>|schools<br>|unor s<br>sch<br>|conary<br>ools<br>|
||No<br>control<br>(1)|Full<br>controls<br>(2)|No<br>control<br>(3)|Full<br>controls<br>(4)|
|**Jakarta Government*Year2015**|-0.51**<br>(0.24)|-0.26<br>(0.25)|2.57***<br>(0.17)|2.61***<br>(0.18)|
|**Jakarta Government*Year2016**|-1.43***<br>(0.29)|-1.25***<br>(0.30)|4.47***<br>(0.36)|4.55***<br>(0.38)|
|Observations|6,849|6,849|2,679|2,679|
|R-squared|0.091|0.101|0.811|0.812|
|No. of Jakarta government schools|1578|1578|280|280|
|No. of comparison schools<sup>a</sup>|705|705|613|613|
|S.D. of 2014 UN score in comparison schools|11|11|7.2|7.2|
|P-value of difference in impact between 2016 and 2015|0.0003|0.001|0.00|0.00|
|Years included|2014-16|2014-16|2014-16|2014-16|
|Controls for students per classroom, teacher education and<br>graduating students|No|Yes|No|Yes|
|Time dummies and school fixed effects|Yes|Yes|Yes|Yes|

Notes: The dependent variable is national examination scores expressed as a percentage. Robust standard errors in parenthesis. *** p<0.01, ** p<0.05, * p<0.1. Comparison schools are non-government schools in Jakarta in columns 1-4. Full results, including the coefficient estimates for the control variables, are reported in Annex Table A1.4.

While further research is required to understand more clearly why the program had a negative impact in primary schools, it may reflect ineffective decision making at the school level. It is possible that the announcement of the program resulted in school principals making changes that had a negative impact, at least in the short term, on student examination results. The limited data available suggest that school principals shifted resources away from hiring temporary teachers and towards improving the condition of classrooms.<sup>18</sup> It is possible that these shifts reduced school

> 17 Annex Table A1.8 also reports results by district for junior secondary schools. They show a similar impact of the program in 2015 across all districts. However, in 2016 the program’s impact in Jakarta Pusat is insignificant and its impact in Jakarta Timur appears much larger than in other districts.

> 18 Data show that government schools reduced the share of temporary teachers in the teaching force from 38 to 34 percent between 2014 and 2016. The share of classrooms in good condition increased from 38 to 47 percent over the same period (see Annex Table A1.3).

15
distribution for the modeling based on the MM5 projections. This means that the probability of insolvency is higher.

<!-- Start of picture text --> x 10-3<br>3<br>2.5<br>2 2016<br>Probability 1.5 2015<br>1 2014<br>2013<br>0.5<br>2012<br>0 Y 2011 ear<br>2010<br>-2000 -1000 0 2009<br>1000 2000 3000 2008<br>4000 5000 2007<br>Ruin Insurance capital/person<br>x 10-4<br>12<br>10<br>8<br>6 2016<br>Probability 4 2015<br>2014<br>2 2013<br>0 2012 Year<br>2011<br>2010<br>-2000<br>-1000 0 2009<br>1000 2000 2008<br>3000<br>Ruin Insurance capital/person 4000 5000 2007<br><!-- End of picture text --> Fig. 7: Simulated trajectories of insurance pool’s capital for the baseline (above) and MM5 scenario (below) over a 10 year time horizon For a more detailed analysis we look at the probability of ruin and the initial capital required to prevent bankruptcy above some predefined threshold level, e.g. increasing the robustness of the pool. In the following, the consequences of mean and variability changes due to climate change for the near future, e.g. 2008 till 2017, and the future period around 2070, based on the information of the MM5 and Precis model, while associated uncertainties and possible implications are discussed.

14
An effective system design is one that is cognizant of larger budget management issues that follows functional and business process requirements of government. System designs that follow predominantly technical considerations, were found to be less effective for solving budget management problems.

The procurement of FMIS systems is complex and warrants careful consideration of a number of issues. Systems specifications in tender documents, the design of the consultancy package, a consolidated systems implementation plan, and contract management experience, were among the most important factors in the process.

Carefully weighing the benefits against risks and costs is important for selecting an appropriate strategy for application software development. Should this include changing technology platforms midway, this involves substantial risks, including loss of human capacity, diversion of reform focus, and neglect of potentially necessary improvements of the legacy system during the transition period.

Experience suggests that system implementation strategies that are strategic and take a phased approach tend to be more successful than attempting simultaneous implementation of a wide set of functionalities as this may overstretch client capacity and dilute the reform momentum. The literature suggests that modules necessary for execution and reporting should be prioritized. Some countries have experimented with taking a modular approach in systems implementation, which holds promise in being more cost-effective.

The implementation strategy may also benefit from prioritizing transaction processing before investing into financial operations and management and reporting layers, since transaction processing is foundational and a prerequisite for the proper functioning of the other layers. If all these are in place, policy makers can use FMIS reports to take strategic decisions regarding the allocation of resources whilst maintaining a fiscally prudent stance. For this however, the system requires full data integrity, which in turn necessitates a reliable transactions processing layer. The usefulness of the financial operations and reporting layer is contingent on this.

The systems deployment strategy across levels of government is a critical phase in implementation. This review found a striking pattern in the transactions profile, with only few transactions making up the bulk of the volume of the budget. This information could be used strategically for early results in the implementation process.

Once operational, adequate budgetary provisions for maintenance and updates are essential for the sustainability of the investment. In some cases, the lack of doing so has resulted in a failure to install timely upgrades, insufficient capacity to manage

**7**

**7**
is numerically far from unity and indicates that the time series are stationary in their first and second differences.

Moreover, upon replication of this procedure with levels of data, the null hypothesis cannot be rejected for all variables with the exception of the change in the nominal exchange rate. This step concludes the existence of strong evidence that all the data series robustly follow an I(1) process in levels, with the exception of the change in the exchange rate that follows an I(0). The quantitative exercise is complemented by visual inspection to double check this conclusion. As seen in graphs (1) for the closed economy specification and (12) for the open economy specification; there are no noticeable structural breaks in the series as it is trending smoothly upward and downwards. This confirms the conclusions from the unit root tests.

# **_Co-integration Analysis- Closed Economy_**

The standard econometric theory concludes that regressions for non-stationary variables give spurious results. The residuals of these models will not be stationary and, accordingly, the standard OLS assumptions will not hold. This applies to the Egyptian data that was tested based on the ADF procedure for integration in the previous section and found to possess unit roots and exhibits integration of first order [I(1)]. However, some linear combination of these series has a lower order of integration. There will also be some (co-integrating) vector of coefficients that forms a stationary linear combination of these variables.

The aforementioned analysis confirmed the fact that levels of all variables are integrated of the same order (I(1)). This is considered the first necessary condition needed to investigate if there is a long run relationship between the variables. The existence of an equilibrium long run relationship between the variables would mean that the variables are co-integrated. The definition of the cointegration relationship can be explained by the fact that it is the set of linear restriction—in other words the linear relationship—by which a number of non-stationary—integrated—series is combined to produce a stationary series. This stationary series is then analyzed to show how variables move and adjust in the long run equilibrium.

The next step to identify the short and long term relations between the variable of interest (real money balances is considered for this paper) is to run a VAR in levels since the five series of the 85