rafmacalaba/datause-encoder-data huggingface dataset:
5 Table 1: Granger-Causality Tests for Current _(CA)_ and Capital _(KA)_ Accounts, 1970-1992.

|_KA_Causes_CA_<br>_CA USKC_|_CA_Causes_KA_<br>_CA USCK_|Neither<br>_CA USN_|
|---|---|---|
|Algeria|Algeria|Bolivia|
|Argentina|Honduras|Barbados|
|Brazil|Indonesia|Chile|
|Costa Rica|Korea|C6te d'Ivoire|
|Greece|Malta|Colombia|
|Kenya|Mexico|Ecuador|
|Malta|Panama|Egypt|
|Mauritius|Portugal|El Salvador|
|Paraguay|Rwanda|Guatemala|
|Peru|Singapore|Jamaica|
|Philippines|Turkey|Malawi|
|Rwanda|Uruguay|Malaysia|
|Singapore||Niger|
|Swaziland||Nigeria|
|Thailand||Saudi Arabia|
|Tunisia||Sierra Leone|
|Venezuela||South Africa|
|||Suriname|
|||Togo.|
|||Trinidad and Tobago|
|||Zambia|

which meant that a wider search for possible **ECM** forms was not feasible. For the same reason, we use only one lag for l ciACAt-. and _Ej'=l djAKAt-j._ In other words, we set both i and j equal to one.

Table 1 shows the results of the initial Granger-causality tests between the current and capital account over the period 1970-1992. Both variables are expressed as proportions of GNP. The capital account Granger-causes current account imbalances in 13 countries and
pricing mechanism at the border as an instrument of protection of domestic production. However, due to the surge in the price of wheat on the international market in 2007 and the need to meet the increasing demand for bread, imports of soft wheat for the production of liberalized flours benefited from import subsidies when prices exceeded the target price.

The high burden of subsidies stemming from the widening gap between domestic and international prices of wheat urged the government to take measures to reduce, albeit marginally, subsidies benefiting the national flour. To this end, it reduced the quota of subsidized flour to 9 million tons annually, while strengthening the control of production and delivery of subsidized flour, and redeploying its distribution to targeted populations, mainly using poverty maps. The government further limited the subsidizedflour’s annual quota to 8.5 million tons starting from the second half of 2013. The reduction of the quota was limited to urban areas with a poverty rate below 10%.

# **3. Baseline data**

The distributional and simulation analyses that follow largely rely on household budget survey data. These data are collected occasionally in Morocco and the last available survey is the 2007 Living Standards Survey (LSS). The first exercise before undertaking the distributional and simulation analyses that follow is therefore to update the information available in the 2007 data to 2014, the year we consider for the analysis. The 2007-2014 extrapolations are based on demographic and economic estimates. Table 4 shows the reference statistics used for the extrapolation.

**Table 4 - Reference statistics 2007-2013**

|Source|**Indicator**|**2007**|**2008**|**2009**|**2010**|**2011**|**2012**|**2013**|
|---|---|---|---|---|---|---|---|---|
|1|GDP<br>(current<br>prices,bn MAD)|616.3|688.8|732.4|764.3|804.2|850.6|909.4|
|1|GDP (real prices<br>1998,bn MAD)|554.0|584.9|613.9|636.6|663.8|688.3|718.0|
|3|GDP<br>growth<br>(base 2007=100)|100.0|105.6|110.8|114.9|119.8|124.3|129.6|
|1|Government<br>spending<br>(current prices,<br>bn MAD)|185.2|219.2|227.7|243.8|277.4|277.0|294.9|
|2|Population (000)|30841.0|31177.0|31514.0|31851.0|32187.0|32522.0|32853.0|
|3|Population<br>growth<br>(base<br>2007)|100.0|101.1|102.2|103.3|104.4|105.5|106.5|
|1|CPI (base 2006)|102.0|106.0|107.0|108.1|109.1|111.3|114.0|
|3|CPI (base 2007)|100.0|103.9|104.9|105.9|106.9|109.0|111.8|

Source: (1) IMF World Economic Outlook database; (2) HCP Morocco; (3) Our estimates. MAD=Moroccan Dirham.

Based on the data presented in Table 4 and the subsequent update of the information available in the household budget survey, we reconstructed population and expenditure figures for the year 2014. These are presented in Table 5. The population of Morocco is estimated at 33.3 million including about 7.1 million families. Total household expenditure is estimated at 580.2 bn. Moroccan Dirham equivalent to 81,743 Dirham per household and 17,420 Dirham per capita. The average household size is estimated 8
where yit is Government Balance, WageBill denotes the public wage bill as a share of GDP, xit is a vector of covariates, and εit is an error term that is again specified as in equation (2). Within xit we include GDP growth as a proximate measure for the state of the economy, population growth to reflect demand for services, and GDP per capita to capture the potential impact of Wagner’s Law (economic development leads to growth in public spending).<sup>9</sup>

**Table** **<u>5: Wage Bill and Fiscal Position</u>**

|Dependent Variable:<br>|Gov_Balanc<br>|eit(General G<br>|ovt Balance,<br>|% of GDP)<br>||
|---|---|---|---|---|---|
|Model|OLS|FE|D-GMM-1|D-GMM-2|D-GMM-3|
||(1)|(2)|(3)|(4)|(5)|
|Gov_Balanceit-1|0.748***|0.347***|0.465***|0.404**|0.919|
||(0.048)|(0.073)|(0.140)|(0.151)|(0.721)|
|WageBillit|-0.041|-0.597**|-0.450**|-0.512**|-0.644|
||(0.061)|(0.238)|(0.201)|(0.187)|(6.795)|
|GDP_Growthit|0.152***|0.165***|0.120*|0.083|-0.048|
||(0.038)|(0.054)|(0.062)|(0.067)|(0.185)|
|Population_Growthit|-0.128|0.436|-0.940|-0.444|0.133|
||(0.203)|(0.341)|(0.607)|(0.565)|(3.187)|
|GDP_Per_Capitait|-0.199|-3.339|-1.070|0.315|-12.319|
||(0.152)|(3.251)|(3.651)|(3.192)|(29.349)|
|Year Effects|Yes|Yes|Yes|Yes|Yes|
|Internal Instruments|No|No|Yes|Yes|Yes|
|# of Instruments|--|--|24|24|24|
|AR(1) Test p-val.|--|--|0.011|0.018|0.164|
|AR(2) Test p-val.|--|--|0.326|0.276|0.187|
|Hansen J Test p-val.|--|--|0.561|0.561|0.967|
|Sample Period|2000-2011|2000-2011|2000-2011|2000-2011|2000-2011|
|Countries|25|25|25|25|19|
|Observations|250|250|225|225|190|

Notes: The unit of observation is a country-year from the sample described in the Data Appendix. Columns (1) and (2) report standard errors clustered at the country level. Column (3) reports one-step difference GMM with clustered standard errors, while column (4) reports two-step GMM whose standard errors have had the Windmeijer correction. Column (5) reports only Western European countries. The internal instrument is the second lag of Wage_Bill_Growthit, and internal instruments are collapsed. ***, **, * indicate statistical significance at the 1%, 5%, 10% levels, respectively.

Table 5 reveals that the effect of the wage bill is negative across all columns and significant for the D-GMM regressions for transition economies, but not for Western European countries. The results from D-GMM-2 show that a one percentage point increase in the wage bill as a share of GDP increases the fiscal deficit by half a percentage point. This finding indicates that it is important to restrain wage bill growth to a manageable level in order to achieve fiscal

> 9 See Heller and Tait (1984).

13
26 Developing small reform teams with staff recruited on a meritocratic basis is another way to bring in the expertise needed to implement reform. Including the core group of technocrats who helped design the reforms in the first place also helps ensure a sense of ownership and continuity, and can enable the process to persist despite changes in the political landscape. In Colombia the core team involved in formulating the 2002 labor market reforms later joined the ministry charged with implementing them. In Mozambique and Peru the small technical teams that designed land reforms continued to facilitate dialogue and implementation. And in Latvia the involvement of the core group of technocrats at the Latvian Development Agency and Bureau of Public Administration Reform allowed implementation to outlast several changes of government.

# **_Revitalizing institutions_**

Creating the right incentives and capacity in several cases required transforming the implementing agencies into new, more service-oriented ones. Pakistan converted the government body responsible for business registration into the Securities and Exchange Commission of Pakistan, a higher-powered, semiautonomous agency backed by a legislative act (box 4). South Africa combined the Customs and Excise and Inland Revenue Departments to form the South Africa Revenue Service. As a semiautonomous agency, the new entity has the authority to set its own human resource policies, establish competitive pay packages, acquire and dispose of property, and impose fees or charges for its services (FIAS 2005j, p. 9). In both cases fresh resources from outside helped bolster the commitment and quality of the existing staff.

In a few cases governments created new implementing agencies to bypass existing agencies that were considered difficult to change. In Peru, where corruption and resistance from bureaucrats and notaries prevented reform of the national land registry in the early 1990s, the government created a new, parallel agency (Cofopri) in 1996 to register informal property and develop the national formalization program. The goal was to shift responsibility for property registration from the municipalities, which had been resisting reform, to a central jurisdiction with decision-making power (Endo 2004, pp. 11–13). Cofopri became an executive branch semi-autonomous agency chaired by a minister of state, reporting directly to the president.
such agreements indicate a degree of economic and/or political proximity to the EU that could be associated either with the use of similar product standards domestically, or the existence of EU aid or technical support aimed at assisting the compliance process. I therefore re-estimate the model excluding (in addition to ATC quota countries) those countries that have a regional trade agreement with the EU, and the African, Caribbean, and Pacific group of countries that benefit from preferential treatment under the Lomé Convention and the Cotonou Agreement.”’ Results are in Table 4 columns 5-6. Estimated coefficients for the two variables of primary interest are in line with those found previously: both are statistically significant at the 5% level, with magnitudes slightly larger in absolute value than those reported in Table 3 column 2. The remaining coefficients are not statistically significant, but generally have signs and magnitudes that are consistent with earlier estimates. The only exception is EU tariffs, which enter column 5 with an unexpected positive sign, and the two ATC liberalization dummies, which enter column 6 with unexpected negative signs. However, given the lack of statistical significance of these coefficients, no strong conclusions are drawn from them at this stage.78 5 Conclusions, Policy Implications, and Future Research This paper has provided the first direct empirical evidence that while product standards overall impact negatively on partner country export variety, international harmonization can act as an important mitigating factor. Based on instrumental variables estimates, I conclude that a 10% increase in the total number of standards leads to a 6% decrease in partner country export variety, but that a 10 percentage point increase in the proportion of internationally harmonized standards leads to a 0.2% increase in export variety. I find evidence that this latter effect is around 50% stronger for low income countries. The empirical results prove to be extremely robust to changes in country sample, °7Data on regional agreements come from http://www.worldtradelaw.net/fta/ftadatabase/ftas.asp, supplemented by information from http://trade.ec.europa.eu/doclib/docs/2006/december/tradoc_111588-.pdf. The list of ACP countries comes from http://ec.europa.eu/development/Geographical/RegionsCountries_en.cfm. 28 An additional issue, not pursued here, is rules of origin. While such measures can undoubtedly impose additional cost burdens on exporters (e.g., Cadot and de Melo, 2007), they are in effect held constant within this sample because only one importing market (the EU) is included. 23
- _The population is still growing rapidly._ Between 1982 and 1994 (which corresponds to the latest census available), the Moroccan population grew by 2,03 percent on average per year ; compared to 2,6 percent during the 1971-82 period. This reduction is essentially imputable to a decrease in the fertility rate (3,28 child per female in 1994). Nevertheless, the population growth rates remains 40 percent higher than the average for middle-income countries. Hence, influenced by the joint effects resulting from the natural growth rate and the rural migration trends, the urban population expanded by 27.7 percent between 1982 and 1994. In 2001, 56 percent of the population is estimated to live in urban areas. In fact, the urbanization of the country is a long term tendency contributing to the labor force growth.

- _Labor supply is growing at a sustained rate._ Within this environment, and considering the demographic structure of the Moroccan population, one of the main challenge in the coming years will be the absorption by the urban labor market of a sustained flow of workers. The pressure is more intense when the situation in the agricultural sector, strongly linked to the climatic situation deteriorates: causing an acceleration in the rural migrations pace, years of weak production are therefore associated with a significant growth in the urban labor force. In the course of the last century, Morocco has experimented, on average, a year of dryness every three years. This confirms that, if it was needed, a sensitive reduction of labor market imbalances can only be outlined on a macroeconomic perspective (and also demographic measures).

- _The potential size of the labor force is significant._ Similarly, women constitute a considerable potential labor force. Indeed, if for specific reasons-education, social status, opportunity cost associated to domestic activities, and so on-their labor supply remains weak, their participation level should increase in the future. In addition, even in the hypothesis of a sustained economic growth, an improvement in the individual perception about the labor market conditions, could contribute to amplify the entry, particularly of women, into the market.

- _Human capital is weak._ The average quality, measured by educational attainments, of the Moroccan active population remains low compared to similar countries. The national illiteracy rate stands at 57.7 percent

18
Saharan Africa, followed by the South Asia region. However, the number of poor people living in poverty is somewhat lower in these two regions under the $1.82 line (by about 10 and 50 million in each of these regions, respectively). The Middle East and North Africa region experienced some of the largest revisions to the PPP data between the 2005 and 2011 ICP rounds, but because of the very low poverty rates at the extreme poverty lines in both 2005 and 2011 PPPs, this matters little for our global results. However, at higher poverty lines, the changes to poverty estimates for this region are much more substantial.<sup>31</sup> While the regional realignment of the profile is significant, it is nonetheless substantially less jarring than with the adjustments made after the release of the 2005 PPP data.

In addition to examining the differences in the regional profile of poverty, it is also useful to compare country-specific poverty rates based on the 2005 PPP (and $1.25 line) with the 2011 PPP (and the $1.82 line). This is not an argument to suggest that the estimates should be assessed on how close they match the existing estimates based on the 2005 PPP data, but rather an exercise to understand how much the profile of poverty would change if the $1.82 line were adopted with the 2011 PPP conversion factors. A bivariate regression between the two rates, where each country is an observation, gives a slope coefficient of 1.00 and an R-squared of 0.95. Similarly, the rank correlation gives a Spearman's rho coefficient of 0.97. The basic bivariate analysis suggests very strong country-by-country correspondence, and Figure 3 illustrates that the change in poverty rates and ranking of countries is reasonably small without many outliers. For 75 percent of the countries, the poverty headcount changes by five percentage points or less

> 31 For example, for a $3 dollar a day poverty line in 2011 PPPs, we estimate a global poverty rate of 32.4% in 2011, similar to the 30.9% for the closely corresponding 2 dollar a day poverty line in 2005 PPPs. However, for the Middle East and North Africa, the corresponding estimates change much more, from 11.4% to 5.4%.

22
with two-part models in the literature (for instance, see Cragg 1971; Dow and Norton 2003; Heckman 1976; Nargis et al. 2013).<sup>7</sup>

# **a. The probability model and the proportion of entrants**

The proposed model exploits the variability of either prices or a welfare variable at the household level (such as consumption) to estimate a probit model of to estimate demand.<sup>8</sup> Assuming independent and normally distributed error terms, and because of a lack of accurate price data in the observations of individuals in household surveys, the probit model is written as follows:<sup>9</sup> P P h h), (1) h,ii �dd �= ff(log (ww ), XX where h denotes a welfare measure (such as income) for household _h_ , and corresponds to a binary variable taking the value of 1 if household _h_ reports positive consumption in good or service _i_ , h,ii ww dd or 0 otherwise. For the sake of simplicity, all explanatory variables are denoted with ; the h and indicators that identify households and goods or services are omitted; and welfare is referred to as XX ii income in the rest of this section, as follows: P P , (2) (dd= 1|XX) = Φ(XX′ββ)

or, alternatively, as follows: where Φ(. ) denotes the normal cumulative distribution function (CDF). Then, the probabilistic elasticity is given by the following: P where I���������� and P�������P refer to the average welfare and average probability of positive consumption at the population level (individual of reference), respectively. IIPPIIuu Taking derivatives and applying the chain rule on the probit model specification, it is possible to rewrite equation (4) as follows:<sup>10</sup>

> 7 The literature on two-part Heckman models focuses on estimating population statistics, such as the change in average quantity, the price elasticity, and so on. In contrast, the proposed framework focuses on the distributional impact of price changes on well-being. Using a Taylor approximation approach, the estimation of the impact on current consumers does not require additional estimates because the necessary information on the expenditures of this group and on price changes is available. However, to estimate the impact on the extensive margin, the consumption decision is modeled conditional on the positive quantities of the good consumed.

> 8 In Stata, the stepwise prefix can be used to perform the selection of explanatory variables automatically according to significance levels.

> 9 If information on the price of the item of interest is available, mcema enables the user to adjust the probability unit model to include price thereby causing the probability of use to be equal to a function of welfare, price, and household characteristics (Rodríguez-Castelán et al. 2021).

> 10 For more information on price elasticity and the two-part Heckman models, see, for instance, Saha, Capps, and Byrne (1997).

5
7 28.0 f 8 23.3 g 9 16.9 h 10 11.6 i

*Using Duncan's test on the average count of NTMs faced. Averages tagged with the same letter of the alphabet are not significantly different.

Similarly, the applied MFN tariffs in the United States and China (taken from the WTO Integrated Database based on the Member's own data notification) tend to be higher for goods produced by poorer workers (based on average wage data from the UNIDO database). Goods produced by workers in the fifth, or richest, quantile face tariffs that are markedly lower than on goods produced by workers from the first, or poorest, quantile across all three countries (Table 8). While the average tariff falls consistently across income groups in China and India, the average US tariff for sectors corresponding to the richest quantile (3.7%) is close to that of the second-poorest quantile (3.8%). However, this appears to be driven by the very high tariff on tobacco.<sup>11</sup> Since the US tariffs on in-quota tobacco imports from selected partners are lower than the tariffs quoted here, the actual applied average duty is lower. Excluding tobacco, the average tariff for the richest quantile is only 0.8%, less than a fifth of the average tariff of the poorest quantile. These results reinforce the view that there is a coordination problem – the "poor" are disadvantaged in terms of market access because trading partners appear to impose trade restrictions disproportionately on sectors that employ poor households.

Table 8. Import tariffs by wage or income quantiles for selected countries

|Wage/Income<br>|Average M<br>|FN for indicat<br>|edyear(%)<br>|
|---|---|---|---|
|Quantile|USA 2008|China 2010|India 2012|
|Q1|4.5|12.7|37.3|
|Q2|3.8|10.9|36.4|
|Q3|3.3|9.8|31.8|
|Q4|2.3|9.3|25.6|
|Q5|3.7*|9.2|14.3|

* This goes down to 0.8% if the high tariff on ISIC 1200 is excluded from the analysis.

# **6. Conclusion**

This paper shows that tariffs tend to be higher and non-tariff measures more prevalent for the poor, thus limiting their opportunities to access international markets.

Countries individually may seek to protect their own "poor" from foreign competition by raising tariffs on the goods these households/individuals produce.<sup>12</sup> There is indeed evidence suggesting that trade policy is biased towards imposing barriers on sectors that employ poor individuals. But, when all countries protect the sectors where the poor work and if the poor are

> 11 In the US some tobacco products have tariffs as high as 350%, corresponding to ISIC 1200, while the average wage in the tobacco sector is very high, with individuals employed in the sector being included in the top quantile of the income distribution.

> 12 This can be the outcome of legitimate concerns, such as the need to protect jobs of workers where labor market frictions or other reasons prevent them from moving to more competitive sectors easily.

15