rafmacalaba/datause-encoder-data huggingface dataset:
# **Table A4: Financial Integration and the Sensitivity of Consumption to Income: Country-Specific Features**

||**Trade In**|**tegration**|**Financial De**|**velopment (I)**|**Financial De**|**velopment (II)**|
|---|---|---|---|---|---|---|
|**_All Countries_**|**Chinn-Ito**<br>**[1]**|**Quinn**<br>**[2]**|**Chinn-Ito**<br>**[3]**|**Quinn**<br>**[4]**|**Chinn-Ito**<br>**[5]**|**Quinn**<br>**[6]**|
|Output|1.058<br>[0.025]***|1.233<br>[0.036]***|0.962<br>[0.017]***|1.124<br>[0.032]***|1.054<br>[0.018]***|1.072<br>[0.023]***|
|Output × _De_<br>_Jure_|**-0.340**<br>[0.027]***|**-0.435**<br>[0.054]***|**-0.516**<br>[0.031]***|**-0.566**<br>[0.059]***|**-0.628**<br>[0.038]***|**-0.335**<br>[0.046]***|
|Output ×<br>_Country Feature_|-0.192<br>[0.029]***|-0.260<br>[0.039]***|0.225<br>[0.021]***|0.088<br>[0.031]***|0.226<br>[0.056]***|0.152<br>[0.031]***|
|Observations|3,436|3,232|3,410|3,207|3,097|3,400|
|Countries|88|85|88|85|87|84|
|**_Advanced Econ_**|**_omies_**||||||
|Output|0.892<br>[0.229]***|1.058<br>[0.236]***|0.839<br>[0.156]***|1.218<br>[0.547]**|0.926<br>[0.264]***|1.247<br>[0.623]**|
|Output × _De_|**-0.390**|**-0.408**|**-0.612**|-0.679|**-0.521**|-0.673|
|_Jure_|[0.215]*|[0.223]*|[0.193]***|[0.641]|[0.262]**|[0.827]|
|Output ×|0.277|0.093|0.415|0.164|0.359|0.175|
|_Country Feature_|[0.125]**|[0.144]|[0.108]***|[0.089]*|[0.174]**|[0.257]|
|Observations|891|909|878|896|807|1,015|
|Countries|22|22|22|22|21|21|
|**_Developing Ec_**|**_onomies_**||||||
|Output|1.031<br>[0.051]***|1.296<br>[0.048]***|0.976<br>[0.040]***|1.142<br>[0.036]***|1.049<br>[0.043]***|1.003<br>[0.055]***|
|Output × _De_|**-0.367**|**-0.457**|**-0.501**|**-0.580**|**-0.679**|**-0.312**|
|_Jure_|[0.061]***|[0.071]***|[0.054]***|[0.074]***|[0.069]***|[0.099]***|
|Output ×|-0.162|-0.328|0.137|0.045|0.211|0.307|
|_Country Feature_|[0.033]***|[0.062]***|[0.073]*|[0.064]|[0.069]***|[0.080]***|
|Observations|2,545|2,323|2,532|2,311|2,290|2,385|
|Countries|66|63|66|63|66|63|

Note: Dependent variable is consumption growth. GMM Dynamic Panel Estimates. Lags 2-4 of consumption growth, all right hand side variables and lagged saving are used as instruments. Country-specific feature refers to trade integration and financial development variables. De Jure refers to financial integration measures of Chinn-Ito and Quinn. In regressions [1]-[6], the _de jure_ and country-specific variables are also used as controls. Trade Integration denotes exports plus imports divided by GDP. Financial Development (I) refers to Private Credit as a share of GDP and Financial Development (II) refers to Financial System Deposits as a share of GDP.

24
overestimates it. Thus, we opt for a middle-of-the-way estimate (shown in the figure) between these two.

Using this estimate, we can correct the Federal primary balance for cyclical revenue effects.<sup>32</sup> This yields the structural primary balance of the Federal government, shown in Figure 4.4. It deteriorated markedly (by nearly 1.5 % of GDP) during the boom period from the end of 1995 to mid 1998, and improved significantly hereafter. The improvement was punctuated by brief periods of relaxation, mostly during the run up to the election at the end of 1999.3

# **Figure 4.4. Current and Structural Primary Budget Balance of Federal Government**

## **(Percentage of potential output and pe rcentage deviation from potential output)**

<!-- Start of picture text --> 3.0<br>2.5<br>2.0 -<br>1.5<br>1.0<br>0.5<br>0.0<br>* 0 * 0 0 0 0 * 0 ~~~m o ol Co<br>-0.5 -<br>-1.0<br>-1.5 -- Primary Balance<br>-2.0 - - Primary Structural Balance<br>-*- Cyclical Component of GDP<br>-2.5 -<br><!-- End of picture text --> Source: Ministerio de Economfa de la Republica Argentina and Ministerio de Obras y Servicios Publicos.

Indeed, estimates of the fiscal impulse, defined as the change in the structural primary deficit relative to GDP, also reveal a significant expansionary change in the stance of the Federal government during the boom period, followed by progressive adjustment after mid 1998 except for a few months in the run up to the 1999 election (Figure 4.5).

**32** To do this, we use a revenue elasticity to cyclical GDP of 1.14, which is obtained from a regression of current revenues on trend and cyclical GDP.

**33** Powell (2002) suggests that inclusion of the Provinces in the analysis would reveal an even larger relaxation in that year.

32
**Policy, Research, and External Affairs**

**S** * S S

**Macroeconomic Adjustment and Growth**

WPS 623 T'his paper - a product of'thle Macrocconiomic Adjustment and Growth Di\ision. Country F.cononltics Department - is part oi' a largcr cftort in PRE to asscss thc clfectivciless ol' ad(justimncit lending. 'oCpics areavailable free from thc World Bank, 181811 Street NW, Washingtonl, D)C2(433. Plca,c contact Aludia Oropesa, room N 1 1-035, cxteinsioni 39075 (37 pages).

Simple comparisons o' growtih rates in countries that have had at least two structural adjusiment loans (SALs) or at least threc adjustincit loans (tlhc first onc in 1985 or betore), show that lheir growth has improved more than that of other countries.

But simple comparisons of the p. ,ormancc of groups of countries aIrc poor cstimattors o' thIc effectiveness of'adjusimcnlt programs because the performance oi' an adjusting country is the result of:

* The policies thait would have been in **place** cven without adjustment loans f'rom thc Bank.

* World economic conditions.

* The effccts of the Bank-supported program.

*Intctnal shocks to the economy (sucil as drought, wars, and earthquakes).

After explicitly controlling for external shocks and nonprogram determinants of' performance, Corbo and Rojas find that adjustment lcnding programs have usually increased the growth rate of GDP and the ratio of'exports to GDP, and have increased the saving-to-GDP ratio over early 1980s levels. But the average ratio of' investimicilt to GD)P has ,'allcn below 1970s levels.

Thc drop in investmncilt's shalre- in GDP in thc initial years ol' adjustmcnt must be initcrprete(l carefully. **In** many countrics, cCoInIollic crisis was the result of unsustainable levels of public investment reachcd in tlhc 1970s: part of' the neede(i a(ijustiiieclt was rc(lucing hligih Icvels ol' inc'ficient public investimicnt. Also, the initial uncertainity that occurs wheln an adjustment program beginis will probably slow do\lon private investmeinlt.

Despite their (disappointing investment performance, these countries expericnccd morc ol' an increase in their rates of' GDP growth in 1985-88 than in 1970-80. This miust rielect mioic cfl'licient invcstment combined with increased capalcity utiliz.ation.

But for countries that havc rcduced miost of' ilicir policy inlef'ficieincies, achicving **an** acceptable, sustaina;lbie grovw1th rate in thec 1990s will require highier investnicnin rates than those achieved in the 190s. **I'lic** chalilcnge ol'lic 1990s is to creatle the coniditionis nec(ded to generate an incrcasc in investnlenl-to-3DlP ratios.

The PRE Working Paper Scries (disseminates **the** findings Of **orTk** un(ter **vsay** in the Bank's **PINhcs,** _Re;alc.li_ and F-iern;iI AffairsComplex. An objectiveof the scries ij lo get thcse findingsoit qutickl. eC cn if preTCentilon'.<sup>;;e 1.ss thln [eih1, miinf hieu.</sup> Thic findin,gs. in terprc tatiotin' **anid** concthi.iomn' **iii** 1dw % iper' do n(it **i** nefe **'** 1fi t r cii o f l zr 13 ink poh(\ IP'odk'''<' h'! thl I'RI: D1),%( ,1.,1nIwI .: (; II, I1.
recent studies of a business simplification program in Mexico (Kaplan et al, 2006 and Bruhn, 2006) did not find much impact of reforms on registration amongst existing microenterprises. This is consistent with the view that firms weigh the costs and benefits of becoming formal, with small firms seeing few benefits.

Our research builds on these existing studies in several important ways. The instrumental variables approach we use here provides a source of identification driven by differences in information across firms, which together with the rich set of owner characteristics as controls, provides a new, and perhaps more credible, approach to identifying the impact of formality. Secondly, this study is the first we are aware of to empirically examine the heterogeneity of impacts by firm size, with our finding of negative impacts on larger firms in particular a new one. Finally, we also examine some of the channels through which tax registration affects profits, which can aid in designing policies intended to make registration more attractive for firms.

The remainder of the paper is structured as follows. Section 2 describes the new survey data used; Section 3 describes the registration process in Bolivia and the measure of formality we choose to focus on; Section 4 provides a simple model of a firm’s formalization decision and uses this to motivate our identification strategy; Section 5 provides the main empirical results; and Section 6 concludes.

# **2. Data**

The data come from the Bolivian _Encuesta de Productividad de Empresas_ , a survey of micro- and small enterprises designed by the authors and carried out during March 2007.<sup>1</sup> The survey covered the four largest cities in Bolivia - La Paz, El Alto, Santa Cruz and Cochabamba – with additional surveying conducted in several rural areas. We restrict our analysis to urban areas in this paper, and in particular, to firms within a 10 kilometer radius of the city’s tax office.<sup>2</sup> The resulting sample consists of 469 firms.

> 1 The survey was conducted by the Bolivian survey firm _Encuestas y Estudios._

> 2 The total sample including rural areas is 629 firms. We also dropped the few firms surveyed which were not owned by the person interviewed (in order that we can control for owner characteristics), and a few firms in transportation with above 20 workers.

- 4 -
# **TECHNICAL APPENDIX**

# **Two Indexes of Price Change**

This technical appendix is based heavily on the discussion of indexes of price change in Pollak (1989), Gupta and others (2000), and U.S. Bureau of Labor Statistics (1997)<sup>22</sup> . The paper uses two measures of the increases in the cost of living or the corresponding fall in real income: one based on an arithmetic index of relative price change, the other is based on a geometric index of price change. These are two widely used measures of relative price change and also underlie recent debates (such as on the U.S. CPI) on how best to account for substitution in measuring relative price change.

The _arithmetic index_ , also known as the Laspeyres index, is a measure of relative price change **R**<sup>**A**</sup> from time _t_ to time _t+1_ , based on a comparison of the sum of weighted prices in time _t+1_ with the sum of the weighted prices in time _t+1_ , keeping the same exact items and the same exact quantities as in the base period in the consumption basket. It is calculated as follows: where _Pt+1,i_ and _Pt,i_ are the prices of the _i_ -th item in the comparison and base periods, respectively, and _Qt,i_ is the quantity of the _i_ -th item consumed in the base period.

> The _geometric index_ is a measure of relative price change **R**<sup>**G**</sup> from time _t_ to time _t+1_ , using the share of consumption items in the household expenditure as weights:

> where _Pt+1,i_ and _Pt,i_ are the prices of the _i_ -th item in the comparison and base periods, respectively, and _wt,i_ is the share of the _i_ -th item in total household expenditure. The relationship of equation (1) to equation (2) can be seen by rewriting the arithmetic or Laspeyres formula as an arithmetic mean of price relatives, weighted by expenditure shares from the base period:

> 22 See also Dalton and others (1998) and Shapiro and Wilcox (1998).

21
# **Appendix 1: Other dimensions of MIC status in historical perspective**

As noted in the introduction, many other socio economic indicators are highly correlated with income per capita; however, relative performance is often on a different scale. For example, access to safe drinking water is either 100 percent or less. In other words, for some access to service measures of development or human capital attainment, one does not have the case of infinitely “moving goalposts,” as discussed above in term of relative MIC status, as measured by income per capita. In addition, technological change implies that there are services today that many MIC residents enjoy that did not even exist in the late 19<sup>th</sup> or early 20<sup>th</sup> century, when today’s HICs were, in fact, MICs by some absolute standard.

Table A1.1 below presents some basic data on the status of middle income countries in a number of non-income dimensions. We see that Upper MICs are reaching over 90 percent access to improved water source and electricity. Life expectancy in Upper MICs is above the US level in 1920 or 1960 and is almost 93 percent the level of the US life expectancy. Even Lower MICs have a life expectancy that is 83 percent of the US level. The infant mortality rate in both Upper and Lower MICs is far lower than it was in the US in 1920, but they still lag pretty badly behind the current US level – especially in Lower MICs which suffer from infant mortality that is over 8 times as high as in the US today. Education variables are lagging as well. In general terms, however, while the history of “catch-up” in per capita incomes is not very favorable, the history on a number of non-income social dimensions is substantially better – at least from the perspective of this brief sketch of some relevant social outcomes.

**Table A1.1: Non-income Dimensions of MICs and Comparison to the United States**

||Upper MIC<br>(2009)|Lower MIC<br>(2009)|US in 1920|US in 1960|US in 2010|
|---|---|---|---|---|---|
|Access to electricity (% of population)|97.3|67.7||||
|Life expectancy at birth, total (years)|72.4|65.2|54.1|67.4|78.2|
|Mortality rate, infant|19.3|50.7|85.8|26|6.5|
|(per 1,000 live births)||||||
|School enrollment, secondary|84.4|59.0|64.3**|84.4**|96.0|
|(% gross)||||||
|School enrollment, secondary (% net)|75.9|52.4*|||89.5|
|Physicians (per 1,000 people)|1.7|0.8|1.37|1.48|2.4|
|Improved water source|91.9|86.5||||
|(% of population with access)||||||
|Literacy Rate (percent)|93.5|70.9|94|97.8***||

Sources: World Development Indicators and Bureau of the Census (1975) Notes: *Data for 2008 instead of 2009 **Slightly different definition: primary and secondary, % of population 5 to 20 years of age ***1959 instead of 1960.

US data for 2010 is from WDI. US data for 1920 and 1960 is from Bureau of the Census (1975).

26
for different categories of events. We use three types of road investment variables in the regression: (1) a dummy indicating if at least one project is ongoing in the cell, (2) a dummy indicating if at least one project has been completed in the cell that year, and (3) a variable that quantifies the stock of road projects happening in that cell. The last variable sums the number of road projects that have happened in the cell including the decay of roads over time. A project that was completed that year takes a value of one, while previously completed projects have a lower weight depending on their decay which is the function of the difference in years since the project was completed.

Table 1: Roads and Armed Conflict

||(1)<br>events|(2)<br>events|(3)<br>events|(4)<br>fatalities|(5)<br>fatalities|(6)<br>fatalities|
|---|---|---|---|---|---|---|
|having an ongoing project|-0.025|||-0.019|||
||(0.016)|||(0.032)|||
|having a completed project||-0.046**|||-0.059||
|||(0.022)|||(0.045)||
|road project stock|||-0.031**|||-0.060**|
||||(0.015)|||(0.027)|
|Observations|18722|18722|18722|18722|18722|18722|
|R2|.402|.402|.403|.348|.348|.348|

Note: * p _<_ 0.05, ** p _<_ 0.01, *** p _<_ 0.001. Standard errors are clustered at the cell level. Cell and year-fixed effects are always included. Events and fatalities are in logs (+1).

We first report the results for the total number of events and fatalities (Table 1). Road projects and violence in the within variation using cell fixed effects are negatively associated. The table shows results for different measures of road project activity and completion. We analyze UCDP events in columns (1) to (3) and UCDP fatalities separately in columns (4) to (6). Columns (1) and (4) show results for ongoing road projects. We see a negative point estimate, which is statistically insignificant. Columns (2) and (5) show results for the year of completion. We find very similar point estimates, but the coefficient is only significant for UCDP events. According to these estimates, the completion of road projects reduces violence by 5 percentage points. Columns (3) and (6) contain our main specification, which tracks the road project stock using the discount factor from the remote sensing exercise. While this indicator does not consider the period before completion, it provides a more accurate estimate of the impact of road rehabilitation projects. First it sums up all projects at the cell level. Second it depreciates the presence of a road over time. We now have statistically significant coefficients for both events and fatalities.

The impact of an ongoing project is weaker and non significant in that specification. The lack of results can be explained by the fact that ongoing projects may have not reduced transport time/cost yet. Ongoing projects can also affect incentives for violence in different ways. They can increase economic opportunities, attract labor and raise the recruitment 21
**Figure (24): Innovation Indicators for MENA and Comparator**

<!-- Start of picture text --> Firms Using Its Own Website<br>Firms Using Technology Licensed from Foreign<br>Companies<br>Firms with Internationally Recognized Quality<br>Certification<br>Firms Offering Formal Training<br>0 10 20 30 40 50 60 70 80<br>Number of patents<br>South Asia Sub-Saharan Africa OECD Middle East & North Africa Eastern Europe & Central Asia East Asia & Pacific<br>Source: World Bank Enterprise Surveys (2007-2011).<br><!-- End of picture text --> The main takeaway from our empirical exercise is that a firms’ success by outperforming other firms in terms of productivity and quality is one key measure of that performance. Innovation through new products and new strategies is a process of elevating productivity and quality. Overall, survey evidence and other indicators suggest that the Arab region lags in innovation, compared to other regions. This is evident in the lack of export diversification, limited productivity growth, and low technological sophistication of exports. An analysis of the investment climate enterprise survey data described above for five countries in the Arab region concluded that firms that had innovated by introducing a new product or upgrading production of an existing one were far more likely to have experienced high growth. Upon the application of analytical models to data that included large firms, three additional factors emerged. Firms that exported more than 10 percent of their sales value were significantly more likely to have experienced high growth than firms that did not. In one model, firms that used email to contact customers and suppliers were significantly more likely to have experienced growth. Finally, in another model, being an SME as opposed to a large firm increased the likelihood of rapid growth.

# **VII. RECOMMENDATIONS AND POLICY IMPLICATIONS—AN AGENDA FOR SHARED PROSPERITY THROUGH JOB CREATION IN THE ARAB WORLD**

Policy makers in the Arab world are working on identifying means of attaining a sustained reduction in unemployment, and achieving inclusive economic growth. With several countries struggling to recover from the recent economic and political developments, job creation policies are at the top of the agenda. It is important for policymakers not only to create more jobs, but also to create better quality jobs to promote growth. Countries in the Arab region are exerting efforts to make their labor force more employable and productive. Without broad-based growth, economies will struggle with social tensions and unrest with a large number of young people who cannot find jobs. The government needs to move promptly, and make policy decisions about how to boost employment, raise wages, and improve productivity.

Governments that are under tremendous pressure to deliver results quickly and are faced with demonstrations, strikes, and social unrest; may overlook longer-term policies focused on creating sustainable, private sector job opportunities and instead consider populist measures that only temporarily address the unemployment problem and alleviate short-term hardship. These 28
the first wave of bankruptcies, finms under this process evidently had higher separations than those outside. This no longer seems to hold for 1993; firms under bankruptcy procedure did not separate more than others.

What about the exit of the larger loss-makers ? For this category (firms with losses >0.1 bnHUF) 292 out of the 603 were in bankruptcy or liquidation but only 5 out of the 41 largest loss-makers. In other words, the bulk of bankruptcies/liquidations were concentrated among relatively small loss-makers.

We can go a bit firther with this and disaggregate in terms of (i) value subtractors (where sales < material costs), (ii) near value subtractors (sales < material + labor costs) and (iii) firms in which sales were greater than material and labor costs combined. Table _5_ shows that at mid-1993, 355 firms in category (i) or (ii) firms were in bankruptcy or liquidation and this accounted for firms making around 50% of total 1992 losses for loss-makers with >HUF 0.1 bn losses.

Using these categories, we can also derive a crude employment decision rule. All employment in value subtracting firms represents an outright loss to society; we assume that this is also pretty much true for category (ii). This sums to 144,000 workers in 1992 or 6.5% of the firm sector. Very crudely (and, probably inappropriately, assuming that none of these jobs could be saved (but ignoring downstream losses) an instantaneous pass-through into unemployment would have jumped the unemployment rate by over 20% at end-1992. As it is, by mid-1993 Table 7 shows that roughly 55% of category (i) and (ii) firms were in either bankruptcy or liquidation procedure. In employment terms, this translates into approximately 73,000 workers; an implicit jump to the unemployment rate of between 10/11%. Continuing our crude line of thinking, we still have an 'employment overhang' from categories (i) and (ii) of c70,000 employees 8 Several tentative conclusions can be drawn at this stage. In the first place, despite a broadly adequate legal framework, there are large lags in enforcement and these are unlikely to be reduced in the short term Second, the bankruptcy and liquidation data confirm the - impression -- indicated earlier of quite significant turnover of finrms, as well as of jobs. In sThis is all very crude, as we ignore any effects via restructuring.

15