OPINION: Growth model and IMF conditionalities — V

While quoting the research of the book ‘A thousand cuts: social spending in the age of austerity’ in the previous part of this series of articles, it was pointed out that there existed a negative correlation between health spending and total number of International Monetary Fund (IMF) programme conditionalities, yet to ascertain whether IMF conditionalities have a causal relation with government health spending, the same book indicated that ‘…a number of political, economic, and social indicators…’ needed to be controlled for reaching ‘…a better understanding of the causal impact of IMF conditionality on government health spending [which, in turn,] necessitates the use of multivariate statistical models…’

Hence, taking data for 195 countries, including Pakistan, over almost two decades, that is, for the period 1995-2017, regression analyses pointed towards existence of a causal relationship whereby ‘on average, each additional binding IMF condition decreases government health spending as a share of GDP by 0.039 percentage points…’ where while most of the causation came from ‘quantitative conditions’ – whereby ‘each additional quantitative condition’ reduced government health spending by 0.035 percentage points — and not ‘structural conditions’.

READ MORE: OPINION: Growth model and IMF conditionalities – IV

Having said, once these conditions were disaggregated, it was found out that within structural conditions, ‘labour policies’ did have a significant negative impact on health spending.

The book pointed out, ‘the point estimate indicates that each additional condition in this policy area reduces government health spending as a share of GDP by 0.230 percentage point…’

Moreover, when IMF condition regarding fiscal balance is also taken as a control, given as the book pointed out: ‘…it could be because we include in our statistical models the government balance (lagged one year), which may be the precise channel by which fiscal policy exerts an influence upon government health spending. By taking it as a control, we effectively block this pathway…’ For this reason, when regression analysis in the book is — done ‘…without controlling for government balance… [it found] a statistically negative effect of fiscal conditions on government health spending as a share of GDP to the tune of 0.263 percentage points per condition.’

Hence, the book indicates that while ‘overall, these analyses show that IMF conditionality does cause reductions in government health spending…’ it could be seen that not only ‘quantitative conditions’ within overall conditionalities, but also structural conditions, like labour policies of the nature of for instance wage caps, or reaching fiscal conditions like primary surplus – a fiscal consolidation, or in the case of Pakistan more appropriately a fiscal austerity condition, given deep extent, and fast pace of adjustment required – negatively impact health spending.

READ MORE: OPINION: Growth model and IMF conditionalities — III

It then shakes the claim otherwise made in IMF programmes that social spending will be protected, given the IMF programme conditionalities inherently reduce this spending, and the higher the number of conditionalities, the more pronounced the impact.

The same book pointed out with regard to the estimated reduction to the tune of 0.035 percentage points (as indicated above) in health spending due to an additional quantitative conditionality, that ‘the mean number of binding conditions, at 24.467 per year, thus corresponds to a reduction of 0.954 percentage points.’

Even so, IMF does not seem to be learning, and it is not clear to the writer of this article as to how much pressure the authorities have placed, for instance, on getting shifted the fiscal consolidation related conditionality from ‘binding’ quantitative performance criteria (QPC), to ‘non-binding’ indicative targets (IT), and, on the other hand, take the IT of meeting floor on health and education spending to the set of binding conditionalities.

This is because whereby as per the recently released ‘IMF Country Report No. 25/332’ while for instance ‘Cumulative floor on general government budgetary health and education spending (billions of Pakistani rupees)’ was being repeatedly missed, ‘Ceiling on the general government primary budget deficit (cumulative, excl. grants, billions of Pakistani rupees)’ was being consistently met, which as per the same country report where it pointed out in one of the footnotes in this regard that ‘Pakistan’s health and education outcomes are among the worst of lower middle-income countries (CR 24/310, Figures 4 and 5), while social protection generosity remains low relative to peers’ highlights difficult realities being faced by the country with regard to health, and education.

READ MORE: OPINION: Growth model and IMF conditionalities — II

Given this situation, one can only imagine that how significantly health spending in Pakistan was impacted in a negative way during 1980-2019. To reach some very rudimentary estimates, based on book’s analysis approximately around 25 conditions resulted in a reduction in government health spending as share of GDP by approximately 1 percent for 195 IMF programme countries, including Pakistan, during 1995-2017.

Hence, given Pakistan faced 1,303 conditionalities during 1980-2019, and in order to have some rudimentary sense of the extent of possible – because 23 years is a significant sub-set from that 40 year time period – negative impact of these conditions on health spending in the country, it is being assumed that half of those conditions were quantitative conditions, which as indicated above explained most of the negative impact on government health expenditure as a share of GDP made by overall conditionalities.

Calculations in this regard indicate that around one-quarter of government health spending as a share of GDP could have been reduced due to IMF’s quantitative conditionalities during 1995-2017; not to mention that as earlier indicated in one of the previous parts of this series, Pakistan was quite low in terms of health spending for countries globally, whereby for both 1995, and 2017 it spent a paltry 0.8 percent of GDP on health.

Not only was Pakistan subject to the highest number of conditionalities for any IMF programme country during 1980-2019, but it remained among the top three countries in terms of number of conditions globally for 1989, 1990, 1992, 2001, 2002, 2003, 2015. In the ongoing EFF programme, Pakistan is facing more than 60 IMF conditions overall.

Yet, there is hardly any discussion on this in policy circles, or media, given such a reduction has profound negative impact on political voice, including in enhancing inequality, both of which are important factors that strengthen demos in meaningfully pushing elites towards doing hard reforms to reduce transaction costs, and overall improve economic institutional, organizational, and market reforms. This, in turn, also takes away credence from the claim made repeatedly by both authorities, and the IMF programme progress reports that these conditionalities bring sustained macroeconomic stabilization, laying, in turn, a solid platform for government to do needed structural reforms, given reduction in social spending, and as subsequent analysis – highlighted in the next paragraphs – from the book highlighted the significantly negative impact of conditionalities in enhancing inequality both are important determinants for bringing sustainability to stabilization, and growth.

READ MORE: Growth model and IMF conditionalities — I

But before discussing impact on inequality, the same book taking the example of West Africa, which consists of 16 least developed countries, which during the period taken as 1995-2017 (or 23 years) were not only in IMF programmes at one time or the other, but where Burkina Faso, and Mali remained in an IMF programme all through the years, with Benin, and Niger stood next as countries being in IMF programmes in 21 of those 23 years. In that sense, these countries are not much dissimilar to Pakistan, which also remained in IMF programmes for many of those years during this time period.

The book pointed out in this regard: ‘The heavy IMF presence in West Africa… averaging 15.3 years of intervention per country in the last two decades, compared to 11.0 in sub-Saharan Africa and 8.0 in low-income countries more generally. IMF recidivism is clearly a prominent feature of the region.

In this period, 12 of the 16 countries experienced IMF conditions for 12 or more years, highlighting the extent to which the IMF has influenced the region’s development trajectory. …For instance, Mauritania was subject to extensive IMF conditionality between 1995 and 1997, and again in 2007, when the country was called upon to implement 73 IMF conditions.’

Similarly, as earlier indicate, not only was Pakistan subject to the highest number of conditionalities for any IMF programme country during 1980-2019, but it remained among the top three countries in terms of number of conditions globally for 1989, 1990, 1992, 2001, 2002, 2003, 2015. In the ongoing EFF programme, Pakistan is facing more than 60 IMF conditions overall.

It is important to note that West Africa, on average, even after being in IMF programmes for so many of those 23 years overall, performed much worse than mean of sub-Saharan Africa in terms of, for instance, Human Development Index (HDI), public health spending as share of GDP, along with public health spending per capita for both 1995, and 2017 on all of these three counts; where average of low-income countries overall was better for all these indicators for those two years than average of sub-Saharan Africa!

(To be concluded…)

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