# The Moorish Wanderer

## The Economic Chronicles of the Kingdom, 1955-2011 Part.2

Posted in Dismal Economics, Moroccan Politics & Economics, Morocco, Read & Heard by Zouhair ABH on July 17, 2012

I should thank Romain Ferrali for his comment/question on some figures I have used on my Capdema presentation (quite a successful gathering, I am told. the Capdema event, obviously) about Morocco’s “1%”.

A challenge indeed, given the scarce information about income distribution from both HCP and the World Bank.

My initial -and strongest- assumption about income distribution is its stability across time: incomes evolve overtime, but the differences between the median and most percentiles relative to their respective incomes are assumed (and tested) to remain constant, or so we shall observe.

A caveat the reader would do well to consider: these incomes are computed on the basis of Gross National Income (from the World Bank Opendata) divided up by the number of households, either provided by HCP census or estimated on the basis of past annual demographic growth. Such a crude method bears several shortcomings in terms of sources of income not accounted for, the heterogeneity of different sources of income, the transfert effects between household to name but three. On the other hand, the primary source of interest remains the dynamics of income distribution, and if indeed additional information arises, I would be glad to carry on and finesse it further. This method might explain why HCP and myself disagree on the definition of “middle classes”: mine is simply the statistical definition of the income halfway between the poor and the rich.

The computations are based essentially on a set of three assumptions:

1/ Income distribution is constant: the same exponential distribution (with different parameter $\lambda$ for each year)

2/ Parameter $\lambda$ i.e. the inverse of GNI per capita, has its own statistical distribution.

3/ the parameter is stationary, possibly with a normal distribution whose mean and variance are estimated on the basis of time series.

An earlier blogpost assumed income distribution was exponential; an educated guess, you might say, given the fact that the decile-based cumulative density function clearly indicates a strong level of inequality – not very scientific indeed, but given the information at hand, it was the best I could come up with. I was lucky enough to find a paper than vindicates partially my assumption.

On income distribution in the United States, Dragulescu & Yakovenko note:

“The exponential Boltzmann-Gibbs distribution naturally applies to the quantities that obey a conservation law, such as energy or money [10]. However, there is no fundamental reason why the sum of incomes (unlike the sum of money) must be conserved. Indeed, income is a term in the time derivative of one’s money balance (the other term is spending). Maybe incomes obey an approximate conservation law, or somehow the distribution of income is simply proportional to the distribution of money, which is exponential [10]. Another explanation involves hierarchy.Groups of people have leaders, which have leaders of a higher order, and so on. The number of people decreases geometrically (exponentially) with the hierarchical level. If individual income increases linearly with the hierarchical level, then the income distribution is exponential.”

The authors provide two possible explanation for that particular distribution: it is either linked to the amount of money at hand, i.e. the higher the income a household earns, the higher its cash-in-hand is going to be, and because money is conserved, income benefits from that effect too. The second explanation is more sociological: income is assumed to have an institutional link to hierarchy, the social and professional status of a particular household confers a certain level of income. Here again, conservation in hierarchical statuses confers on income the same distribution.

The exponential distribution is a very useful statistical device. Its density function needs only one parameter, and is defined such:

$f(x) = \lambda \exp^{-\lambda x}, x>0, \lambda>0$

the restrictions on x is useless in this particular case, since income is obviously a positive amount of money, and lambda is necessarily positive, since:

$\mathbb{E}(x) = \frac{1}{\lambda}$

and there lies the usefulness of the said distribution: all we need is a time series of GNI per Capita or per Household to generate yearly income distribution. The idea is to use these as random vectors to check the effects of inequality over a long period of time. Once this set of distribution is generated, we test the results against empirical data from 1985, 1991, 1999, 2001, 2007 and 2010.  (available on the World Bank data nomenclature) The data at hand is the decile/quantile distribution of concentrated income.

we test whether differences in both values for available years are not statistically significant. Don’t bother with seemingly larger differences for 2007 and 2010, the sample size puts it in perspective.

If the three assumptions turn out to be correct, we should observe generated results close enough to empirical percentages from these years, and thus conclude to the robustness of the estimated income distribution. The policy implications of these results are infinite: fiscal policy, among others, would gain a lot from addressing issues of truth-telling and other institutional dysfunctions. But for now, I am focused on trying to describe as explicitly as possible statistical properties of income households in Morocco since its independence.

A first test to check whether income distribution is exponential, is to compare synthetic and empirical median income per household. The exponential distribution has the following property:

$\int_{0}^{x}\left(\lambda \exp^{-\lambda t}\right)dt= 0.5 = median$

which means the difference (or ratio) between average and median income per household is a constant commensurate to $ln(2)$ the null hypothesis in this case is to check whether observed discrepancies between both datasets are statistically insignificant. At 95% confidence interval, we get most empirical values lay between the 45-52% percentiles, which, given the size of the selected samples, is a pretty robust evidence these differences amount to very little. We therefore retain at high levels of confidence the assumption of the exponential distribution.

For instance, median income in synthetic data for 1985 was 23,293 dirhams, vs empirical median income of 24,210 dirhams, which falls within the 51%-52% percentile (which is more than enough to test at 95% confidence). It is worth pointing out however that these discrepancies, for all their statistical irrelevance, are systematically in favour of empirical data, which points out to an income distribution marginally more unequal than the exponential distribution suggests. However, because the fit is robust enough, we shall settle for the synthetic model. A final caveat perhaps: the test was carried on 6 particular dates, which still does not preclude significantly different results for the 51 remaining years. The likelihood of such event nonetheless is very low in view of the levels of confidence used earlier.

The fact the distribution has been the same (with its parameter $\lambda$ evolving with GNI per household) since 1955 might lead to think that income inequality has remained constant since 1955 (recall the ratio Median/Mean is $\log(2)$) and for some inter-quartile ratios,  results are stationary, which means inter-quartile income inequality has not change significantly over the past half a century.

large discrepancies between the top 1% and the median incomes starting from the 1970s

The picture is not all that clear, though: first off, the upper bound evolves frequently, a properties that has to do with the elusive nature of high income households (the 1% more affluent) the synthetic income distribution. If anything, there seem to be no particular link that growth since 1955 has contributed to influence income inequality one way or the other. What looks to be painfully clear however, is that the richest 1% have enjoyed a distribution of income growth whose trend is undoubtedly in their favour: between 1955 and 2010, the richest 1% have improved their income relative to all percentiles below the median by 6%, even as GNI per Household grew an average 6.91% over the same period of time. It might look like jumping to conclusions, but unequal distribution of income growth seem to contribute a lot, if indeed 86% of it goes to the top 1%.

I would say the graph and these computations understate the discrepancies between top and ‘regular’ earners: the sample size goes only as far as list maximum values of an annual income of 1,077,000 dirhams per annum, even as rarefied incomes are larger by far. If anything, these computations would instead minimize the reality of income inequality, because extreme values on the right hand-side tail are bounded.

So there it is: a quick look at the relationship between growth and inequality indices point to the lack of correlation: growth in Morocco does not necessarily bring about better quality of life to households below the median line. If anything (but the statistics gets blurry there) income inequality abated during the 1990s (a period of recession as well as structural reforms) and increased with the early 2000s (an economic expansion by many measures)

## The Economic Chronicles of the Kingdom, 1955-2011 Part.1

Posted in Dismal Economics, Moroccan Politics & Economics, Morocco, Read & Heard by Zouhair ABH on July 12, 2012

It’s been a long time I did not show up on twitter, and I am the better for it. I wouldn’t pretend I’d missed the impassioned twitto-debates I have been involved in, but in matters of economics -as much as in other areas- complex issues cannot be boiled down to 140 characters.

Summertime and with it comes time for self-assessment. A lull to reflect on the past year.and I would like to devote part of my time to a dear project of mine, one that I would like to devote my professional life to: a comprehensive chronicle of Moroccan economics, from the mid-1950s up to date. This I would like to do because the mainstream documentation on that subject and other contiguous ones is not, to my opinion, satisfactory. This is by no mean unfair criticism of their authors, often reputable scholars that however fell victim to trivia and the politically correct. But the fact remains, there are very few papers I can lay my hands on that resemble anything close to, say whatever Lucas, Sargent, Prescott, Kydland, Blanchard, Krugman (to name but a few über-heavyweights) produced in macroeconomics. I am sorry the Cinquantenaire report and the paper commissioned by the Abderrahim Bouabid Foundation did not rise up to the challenge. At least I will not disappoint as a pseudo-amateurish academic blogger, will I?

I suppose it is extraordinarily pretentious of me to even assume I can write up Morocco’s economic history. And surely it is. But my amibition is otherwise: I wouldn’t like to merely report on economic facts and statistics – for that and many other useful comments, please refer to the never boring Annuaire d’Afrique du Nord. As a matter of fact, it is because I had the pleasure of reading some of their earlier issues on electoral results from the 1963 general election, that I though I can take a look at data circa 1950s-1960s and confort it to mainstream macroeconomic models: what went wrong, what went right. You see, the Moroccan economy as a whole tends to exhibit steady properties. That says a lot about some policies and their effect on the economy, but still. What an orthodox Marxist sees as the inevitable dynamic of History (capital H, as in Hegel) I would suggest measurable economic forces have been at work.

What development means: a simple case study.

The problem at hand as far as the Moroccan economy goes is how it fares relative to the rest of the world, and more precisely, how it does relative to advanced economies. I had the opportunity to present the reader with some blogposts on the matter, but back then I lacked the adequate skills to put a convincing argument to my claim. I don’t implying I fully master these skills, but the analysis is definitely getting better.

Development in its crudest definition means simply the (accelerated) accumulation of physical goods, or capital. One may disagree with it (if anyone is interested, Joe Stiglitz, Amartya Sen and JP Fitoussi produced an interesting report on Gross National Happiness) but as long as no credible alternative analysis to the theory of capital accumulation, we should go with the existing. So the faster an economy cumulates capital (in real terms) the better it is, and the more developed it eventually turns out to be.

Keeping up with pre-1977 levels of growth could have made Morocco 39.87 Billion dirhams in real terms, and double our GDP per capita by the end of the 20th century

But, in order to do so, one needs a yardstick to measure that progress. I would like to consider reusing the comparison to the United States, to which I would like to add South Korea in the mix, and start off with a graph depicting real GDP per Capita in these three countries from 1955 to 2000. Morocco’s GDP is supplemented with a fitted estimation of its annual growth with pre-19777 levels (and variance)

The graph shows compelling evidence as to how Morocco does with respect to that convergence theory: Morocco had, up to 1977, levels of growth fit to carry us to significantly higher levels of income, aggregate and per capita. Indeed, between 1955 and 1977, average real GDP per capita growth was around 7.4%, and decreases to 6.4% from 1977 to 2000, a full percentage point lost in 23 years.

This is so-called Beta-convergence: because Morocco was a poor country in 1955 and 1977 by any measure, it is assumed it will grow at a faster pace, so as to catch up to more advanced economies; by comparison, the US economy (per capita) grew 6.4% between 1955 and 1977, and the South Korean economy, 7.1%. If anything, up to 1977, Morocco was doing pretty well. This begs the question: what did go wrong? Why didn’t Morocco maintain its average growth pre-1977, and does it really matter?

Perhaps it is not all about higher levels of growth. Professor Najib Akesbi, an eminent contributor in both reports mentioned earlier, did confirm his preference for the Beta-convergence theory: He believes -correctly- the economy needs an annual rate around 8% to achieve levels of income observed in big emerging economies; actually, when demographic growth is taken into account (around 1%) the level of growth to which Prof. Akesbi refers is the magic, pre-1977 growth per capita.

Let us test that hypothesis: let us assume that indeed, Morocco has been growing at annual level of 7% between 1955 and 2000 at around 3.8%. We then look at the gap between synthetic and empirical data. Results seem to contradict Professor Akesbi’s claim: for Morocco to achieve an annual 7% since 1955 results in a net real gain of 17.1Bn dirhams, and real GDP per capita would only increase 60%. So the Beta-converge does not explain Morocco’s failure to establish itself as a promising and dynamic emerging market; it is not enough to achieve high levels of growth. Sure, it definitely provides a higher GDP per capita, but not up to levels worth supporting the case for unconditional high growth. Something is definitely wrong with that crude theory of capital accumulation. And I would like to read some paper from mainstream economists here on the virtues of the other way to achieve higher levels of output per capita: the Sigma-convergence, or steady reduction in output volatility.

Strong growth 7% loses 40% of its effect to historical volatility. That number alone does not mean much.

In statistics, standard deviation provides a measure of how far apart individual observations are from the mean. If standard deviation is high, that mean… means nothing. In our particular case, a high level of output tends to lose some of the accumulated effects of high growth rate: doing 6% on a row for two years yields 6%. doing 0% and then 12% yields a real growth of 5.8%, since:

$y_t = \sqrt[t]{\prod_{i=1}^{t}(1+y_i)}$

The standard definition of a geometric mean suits growth levels better because it is just another application of compounding interest rates. Besides, it also captures precisely the cost of an unconditional Beta-convergence, in our particular case, the 7% with historical volatility (standard deviation) advocated earlier turns out to be 6.6%, and .4% is not a marginal quantity, it amounts to about 2.4Bn dirhams, in real terms. These are lost because the economy cannot sustain itself at 7% over a long period of time.

This, in my opinion, is Morocco’s conundrum: it needs higher levels of growth than those observed during the last decade (and that explains why I restrained my comparisons to 1955-2000) so as to boost its GDP per capita. On the other hand, it cannot achieve it without high levels of volatility that would ultimately take away substantial amounts of that high growth. The balanced growth path needs to be found elsewhere: in each aggregate contribution to growth, among others.

## “Gouverner, C’est Pleuvoir”… Or Not

Posted in Dismal Economics, Moroccan Politics & Economics, Morocco by Zouhair ABH on July 9, 2012

An excerpt from the 1967 issue of ‘Annuaire d’Afrique du Nord’ on the Moroccan economy:

L’augmentation de la production agricole en 1967 par rapport à 1966 a donc été due à peu près intégralement à des conditions climatiques plus favorables, c’est-à-dire à un facteur exogène; nous savons par ailleurs qu’en valeur absolue l’augmentation de la P.I.B. de l’agriculture n’a représenté que la moitié de l’augmentation de la P.I.B. du Maroc par rapport à 1966(8). Analysons donc maintenant les facteurs endogènes qui ont permis aux autres branches d’activité de contribuer pour moitié au supplément de production obtenu.

[…]

Tel est le secteur agricole, sur lequel les autorités comptent pour réaliser le décallage de l’économie : très instable du point de vue conjoncturel et ne montrant aucune tendance marquée à l’amélioration des rendements, en tous cas à peu près insensible d’une année sur l’autre aux incitations qui lui sont prodiguées sous formes d’encouragements, de mesures administratives ou d’investissements.

My (belated) interest in Moroccan agriculture finds its origin in the topic of Moroccan business cycles: as far as I can tell, fluctuations in agricultural output do not seem to have that big an impact on aggregate output. This means poor economic performances are not necessarily always due to drought or weak agricultural production. In that sense at least, “Gouverner, C’est Pleuvoir” maxim dear to Maréchal Lyautey bears little significance other than the political strategy it sustains: rural labour market in Morocco is very homogeneous and volatile, which only means a large fraction of the population -in fact, a majority- depends on random meteorological wonders. Since the early 1990s however, the urban workforce has come to encompass a majority the current demographic trend predict to be irreversible. Nonetheless, “Grands Barrages” and “Plan Maroc Vert” are both similar in their imposed, top-down implementation, as well as their disregard for institutional constraints, likely to jeopardise their initial objectives; A report from 1975 mentioned:

Le modèle d’aménagement qui a toujours la faveur des services responsables est celui là même qui avait été établi par l’ONI. Or, pour l’ONI, le choix de cette formule correspondait à un pari sur changement de structures que semblait autoriser dans l’esprit des responsables le contexte politique de l’époque. Le pari a été perdu mais, assez curieusement, le schéma d’aménagement servi par une logique technicienne extrêmement séduisante s’est maintenu comme un dogme de la mise en valeur.

the scheme anticipated by the Office National d’Irrigation (ONI) pre-dated the policy itself, and finds its roots in the early rural policies of 1958-1960, and these had in mind a deep structural reform of real estate regimen. These reforms, for (obvious) political reasons, were quickly shoved in favour of a status-quo that still prevails. In that respect, there are very few farmers eligible to benefit from these decision, and those who might have qualified did not really need the subsidies. the Grand Dams did not come alone: a series of state-sponsored programs were put together to help farmers by subsidising particular goods (especially sugar) and providing support on the basis of expected returns. Unfortunately, the report points out that only very few endeavours managed to reach the theoretical threshold of 1,500 to 2,000 dirhams/ha.

A Gini Index of 3.76, a relatively high number for inequality in distribution, which vindicates the claim agriculture is concentrated in the hands of the wealthy few

Assuming figures from the 1996 Agricultural Census did not change dramatically – though there is every chance these have indeed- any top-down policy will benefit about 12.3% of all farmers: there should be around 1.4 million farms (down from 1.5 million in 1996) whose distribution shows a great deal of discrepancies: there are about 12.3% of all farmers (around 185,000) that concentrate more than half (54.4%) of arable lands, these usually cover large surfaces, typically no less than 10ha. These lands are undoubtedly the best equipped and the most productive: the 12.3% lucky few concentrate 86% of all available tractors and 87% of harvester machineries.

These large farms tends also to be more capital-intensive than the others as well as the national means: they use about twice as much machinery, and three times as much new technology, including new types of fertilizers and selected crops.

These are 1996 figures; and yet it is on the basis of these figures the Grand Design is carried out. In fairness, the explicit working assumption behind the PMV strategy is to concentrate 80% of allocated resources around less than 40% (wealthy) farmers. Trickle-down at its worse:

And Plan Maroc Vert (PMV) suggests these wealthy farmers ‘share’ their capital with their poor neighbours:

6. Autour de quoi peut-on s’agréger ?

L’agrégation peut s’effectuer autour de différentes opérations ou services liés au processus de production et de valorisation d’un produit tel que :

– L’acquisition ou l’utilisation groupée d’un matériel agricole ;

– L’équipement en commun en systèmes d’irrigation, en système collectif d’avertissement et de lutte contre les aléas climatiques ;

– La réalisation d’une prestation commune (labour, traitement phytosanitaire, irrigation, récolte…) ;

– Le stockage en commun ;

– La valorisation de la production ;

L’idéale, serait l’agrégation autour de l’ensemble du processus de production de l’amont à l’aval pour bénéficier de la marge de l’ensemble des chaînes de valeur.

The plan does have a sub-strategy for smaller, poorer farmers, the so-called “Pilier II”:

* La stratégie du Pilier I se traduit par la réalisation de 961 projets d’agrégation et vise 562 000 exploitants moyennant un investissement global de 75 milliards de MAD

* Aussi, le Pilier II envisage la réalisation de 545 projets sociaux en faveur de 855 000 exploitants pour un investissement de 20 milliards de MAD.

(please note the second part of the program is a set of welfare projects, contrary to the other, supposedly more “serious” investment projects)

In many respects, the Grand Dams and the attached policies have failed to boost productivity per agricultural worker, precisely because these have been concentrated on a few farms; if anything, agricultural productivity per capita increased in volatility with the early 1970s. Per previous experiences, and on the basis of similar assumptions and data, concentrating (aggregating, as it were) resources in the hands of the rural establishment does not do good for the remaining many. I hope the chaps over at McKinsey though about it carefully.

A quick word perhaps on the correlation between agricultural, non-agricultural and aggregate output: by my account, all robust correlations point out to a strong relationship between aggregate and non-agricultural output (.953) much stronger and more significant than that with agricultural output (.619) and there is an even weaker correlation between non-agricultural and agricultural outputs (.369) and these correlations change significantly when considering only the period 1955-1975.

Morocco was a ‘pure’ agricultural country up to the mid-1970s: a majority of the labour force was employed in  rural activities, and there was a much tighter correlation between rural and urban economic activities. Nowadays, the only remaining feature is the disproportionate percentage of labour force employed in the rural sector. Agriculture, in that sense, modernized, but the trickle-down effects of past (and future) policies are yet to show their benefits to the many farmers.

## يسار يسير و عسير

Posted in Moroccan Politics & Economics, Moroccanology, Read & Heard, Wandering Thoughts by Zouhair ABH on July 7, 2012

## ‘Plan Maroc Vert’ – Grand Dams Redux?

Morocco’s Godwin Law evolves usually around the Big Dams built during the late 1960s and 1970s to burnish the economic legacy of King Hassan II.

La politique des barrages lancée par Feu Sa Majesté le Roi Hassan II dès 1967 traduit la pertinence des choix stratégiques opérés en matière de développement économique et social et de valorisation des potentialités agricoles du pays à travers le développement de l’irrigation.

(Rapport Cinquentenaire – Ressources en eau et bassins versants du Maroc : 50 ans de développement)

It also serves as the opening gambit for the strategy to justify nowadays’ “Grands Chantiers” policy. Let me go on the record to state my complete adherence to a policy designed to improve and expand public infrastructure with large public investment. There is nothing wrong with it, quite the contrary. However, the snag with the Grands Chantiers is essentially institutional: I suppose the benevolent authority only goes as far in its benevolence as its own interest lies in the mechanism design it enforce. Unfortunately, there is ample evidence that a benevolent authority in Morocco doesn’t exist: once a player gets to set the rules, these are bound to be bent to their advantages.

But this does not fall within the purview of my post today; I have had a bit of a difficulty to gather data on the matter, but here it is. In a nutshell, I am interested in the dynamics of Agricultural and Non-Agricultural GDP per effective worker since 1955. The (big) Dams have been built with the ostentatious purpose of improving agricultural output by storing and distributing water. As one might assume, such investment should have led to an increased productivity per agricultural worker: after all, production in that particular subject is subject to diminishing returns (because of the fixed stock of land) and improving the use of a vital input should, at least on paper, increase productivity per worker over time. I am no expert in agricultural economics, but there are some properties one can observe across all productive sectors: building the dams should have a positive impact on productivity per worker; otherwise, why bother spending billions of Dirhams?

Base year 1955: Non agricultural output per worker increased 7 folds. Agricultural output per worker only doubled.

To compute productivity per worker means to first split total labour force and output into agricultural and non-agricultural, and compute their respective ratios (which is no easy task since HCP does not provide data on 1955-1959) and then plot their annual growth with 1955 as base year. Output per worker radically diverges right from the early years, from 1958 to be precise.

By 2011, the gap increased to the point where an agricultural worker has to work 5 times as much to match the output produced by their non-agricultural opposite number. Not only that, but agriculture in Morocco did not improve its productivity since it has stagnated; it has exhibited an average real productivity growth rate of 1,23% versus 3,71% for the other sector. In that respect at least, dams did not do very well.

Perhaps a case can be made as to the way I have computed agricultural productivity; after all, if rural population exhibits higher demographic growth, the ratio is flawed since rural labour market is a lot more homogeneous than national or urban markets, and hence demographic growth is akin to annual growth in the labour force. If anything, rural population has proven to increase at significantly lower levels compared to nationwide and urban growth. So this precludes a demographic caveat: productivity in Morocco’s rural fields is lagging, even as the whole economy grew and made use of technological change. So, did the dams do well? To check if these have been useful, we would expect a gradual cut in output volatility. After all, much of output fluctuations (especially in Morocco) is due to rain forecast (although that particular argument is bound to be discussed too) and the dams were there precisely to alleviate the randomness of rain seasons.

Before 1967, logged agricultural output per worker was around 9.14% and gradually increases to 10.68% for an average volatility around 10.21% an empirical evidence strong enough to conclude that agricultural output grew more volatile after the dams were built. Though there is no proof of definite correlation between both events, it is safe to say that these public investments failed to achieve their initial aim. If anything, the dams and the agricultural policy pursued since then hurts the vast majority of the Moroccan farmers. The quantitative impact of these policies remains to be published by the relevant authorities.

In that respect, agricultural GDP has been a drag on the aggregate growth, because it has failed to go beyond their structural diminishing returns. It has been a drag because in the final analysis, aggregate productivity is closer to that of rural sectors, which implies disproportionate concentration of technology in one sector and deprive the other actual weakens the sum of both. In that sense, to improve GDP growth means bigger technological changes in rural output per worker.

Plan Maroc Vert has made it clear their main action allocates 80% of its funds to the top 20% already modern, mechanized and export-oriented agribusiness industries (). This concentration in technology is similar to the failed experiences carried out ever since 1958, because it will confirm strong incumbents and at the same time submit smaller farmers permanently.