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Make ‘em Prove the Causality before They Cause Any More Suffering: Part Three, Reinhart – Rogoff Retrospective

7:31 am in Uncategorized by letsgetitdone

This post is a more complete statement of my conclusions based on the analysis in Parts One and Two of this series. As I’ve explained in Part Two, there’s no reason in the Reinhart-Rogoff (R-R) data to believe that the debt-to-GDP ratio has a negative impact on growth. Ironically, that’s because their data set is terribly biased in its incompleteness, and was constructed to try to prove that there was a negative relationship between the debt-to-GDP ratio and economic growth. The interests supporting the RR work, both in its inception, and in disseminating its original results, were clearly trying to develop a basis for saying that since there is such a negative relationship, the right thing to do when the ratio gets too high (over 90%) is to implement a program of austerity aimed at deficit reduction, more or less drastic, depending on the individual case.

Of course, there may well be a relationship between debt-to-GDP ratios and economic growth in nations lacking non-convertible fiat currencies and floating exchange rates, and and/or having external debts in currencies they cannot issue. However, the R-R data set didn’t include those variables, so that analysis can’t be done without augmenting the data set. In such nations, MMT theory suggests that Government Budget Constraints (GBCs) on deficit spending, such as those we find in Eurozone nations would create a negative relationship between debt-to-GDP ratios and growth.

In fiat sovereign nations, such as the US, the UK, Australia, Japan, etc. we might also have the presence of an indirect relationship between variations in the debt-to-GDP ratio and economic growth through the actions of politicians who believe in austerity ideology pulling back on government deficit spending and consequently having a negative impact on economic growth through that mechanism. But to test for that self-fulfilling prophecy, and also for the negative relationship in nations subject to a GBC, someone will, again, have to augment the R-R data set and re-analyze it to include currency regime variables

In addition, we need to build on the biased and incomplete R-R data set to begin to test alternative hypotheses about the effects of austerity and different types of fiscal and monetary policy on different outcome variables and on feedback relationships from those outcome variables to economic growth and much more. When Matthew Berg and Brian Hartley say: “We suggest that simultaneous equations models may offer a way forward on the “frontier question” of causality,” they are also saying that other possible causes of both economic growth and debt-to-GDP ratios must be included in richer theories of economic dynamics, if we want to understand the place of both growth and debt in the broader context of what matters to people.

What matters to them are economic and social value gaps related to the idea of Public purpose like these:

– the gap between actual output and projected “full” output;

– High involuntary unemployment vs. full employment;

– Price stability vs. inflation or hyperinflation;

– Minimum wage vs. a living wage;

– No operative right to health care for everyone;

– social exclusion and the loss of personal freedom;

– skill deterioration due to unemployment;

– psychological harm such as sense of identity, self-respect, and sense of
empowerment;

– much greater ill health and reduced life expectancy than necessary;

– loss of motivation to live a full empowered life;

– deterioration of social relations, communities, social networks, and family life;

– increasing racial and gender inequality;

– increasing educational inequality;

– decreasing equality of opportunity;

– loss of social values and sense of individual responsibility;

– increasing economic inequality over time;

– increasing poverty;

– increasing crime rates including increasing use of control frauds by
important economic institutions;

– Failure to prosecute and punish people who commit control frauds;

– The collapse of real estate values and the destruction of the wealth of
working people after the crash of 2008;

– increasing anger against economic and political elites that get more and
more and more wealthy, and more and more immune to the rule of law;

– increasing political inequality undermining political, social, and economic democracy;

– increasing political unrest and threats of political violence both from the privileged and those seeking change.

– increasing environmental degradation;

– Increasing climate change/global warming.

– the gap between current energy foundations of our economy and new energy foundations based on renewables.

It will involve more of an effort to gather the necessary data in some of these areas than in others, and doing this kind of thing is a multi-year job. But it’s imperative that something like it gets done, because the kind of narrowly focused data set created by R-R is biased towards the concern of neoliberal ideology with debts, deficits, inflation, and economic growth, and its lack of concern with the impact of its favored economic policies on a range of outcomes important for most people. We need to be gathering data on those outcomes and analyzing the past, present, and likely impacts of alternative fiscal and monetary policies on them. In short, we need to be gathering data that allows us to test the impact of alternative fiscal policies on public purpose.

Finally, we must ask why there wasn’t a greater outcry from progressive activists and economists when the R-R study first appeared and they failed to make their data available for re-analysis and replication. After all, everyone who read their work and who knows even a little about quantitative analysis in the social sciences could see that it was based on a very superficial two-variable cross-country global data analysis, and that any result they reported had to present a false picture of causality.

This is true because you can’t provide a thorough analysis of causality between two cross-country variables without including additional variables and doing time series analysis at the national level to establish causal ordering and partial out spurious correlations. This has been well-known in the social sciences for at least 50 years.

MMT economist Randy Wray has called the R-R study “crap.” He’s right; for all the reasons just advanced, it was crap from the get-go. It presents an argument of partisan advocacy, not one of economic scientists making a conscientious effort to get at the truth.

So, the question is why has it been it challenged so little since 2010? It’s true that some economists provided critiques. But the discipline as a whole was respectful. The criticism was civil, when it should have expressed outrage. Everyone treated the critical exchanges as a matter of “he said, she said,” even though every economist who does any data analysis must have recognized the very simplistic level of R-R’s data analysis.

So, again I ask, why didn’t economists make ‘em prove it? And why did policy makers accept the findings so easily? You can’t tell me that the top economists in the Obama Administration, in the UK, and the Eurozone couldn’t see the nakedness of their co-emperors. They chose not to see.

I think there’s really no mystery here. Neoliberal elites wanted to believe in the austerity fairy tale for various reasons, including perhaps a desire to widen the wealth gap between the very rich and the middle class, and also a belief that belt-tightening in welfare states has moral value for the population subjected to that belt-tightening, though not for them, of course. For them, R-R was just window dressing for the financial sadism they wanted to implement anyway. If you doubt this characterization, then pay close attention to interviews of Erskine Bowles and Alan Simpson sometime. The are exhibit A.

But for the progressives, and others opposed to austerity, the R-R work should have immediately become a target of opportunity for educating the public about “junk” economic studies relied upon by politicians to justify their favored policies. Opposition to the study should have taken the form of telling people never to trust simplistic two variable analyses using cross-sectional rather than time series data to develop causal explanations. It should have taken the form of a demand for the economists and policy makers to prove what they say rather than just wave around a fig leaf that couldn’t possibly, and in the end did not, prove a thing about the desirability of austerity in modern economies.

But none of this occurred. And partly as result of this dog who never barked, millions around the world live with economic hardship lasting for years. Millions lost their homes. Millions went into bankruptcy, and many thousands needlessly died from lack of medical care and are still dying today.

(Cross-posted from New Economic Perspectives.)

Make ‘em Prove the Causality before They Cause Any More Suffering: Part Two, the Fall and After

11:18 am in Uncategorized by letsgetitdone

In Part One, I asked whether the Carmen Reinhart/Kenneth Rogoff study and book didn’t show that, on average, nations experiencing debt-to-GDP ratios above 90% had negative rates of economic growth? And I said the answer to the question was “no.” But I didn’t explain why that was true. So, here goes.

The Fall

When Reinhart and Rogoff published their work they did not make their data set available to people to replicate, analyze, critique their findings, and augment to improve the data set. They ignored the scientific norm that you do that when you’re claiming that you’ve made an important empirical discovery. Other researchers wrote them and requested access to their data set in vain for at least the past three years.

Then a few weeks, ago, they finally yielded to a request for the data set made by Thomas Herndon, a Graduate Student in economics at the University of Massachusetts (UMass) in Amherst. Herndon tried to replicate their analysis and findings and could not do so. In fact he found errors. Here’s a summary from the paper he co-authored with two of his professors, Michael Ash, and Robert Pollin, both of the economics department (hereafter called HAP).

RR has made significant errors in reaching the conclusion that countries facing public debt to GDP ratios above 90 percent will experience a major decline in GDP growth.9 The key identified errors in RR, including spreadsheet errors, omission of available data, weighting, and transcription, reduced the measured average GDP growth of countries in the high public debt category. The full extent of those errors transforms the reality of modestly diminished average GDP growth rates for countries carrying high levels of public debt into a false image that high public debt ratios inevitably entail sharp declines in GDP growth.

Moreover, as we show, there is a wide range of GDP growth performances at every level of public debt among the 20 advanced economies that RR survey.

Specifically, “actual average real growth in the high public debt category is +2:2 percent per year compared to the -0.1 percent per year published in RR.” That change in the findings is very important because even though the new average growth level found is still less than in the 60% to 90% category, where the average growth found was 3.2% annually, the claim that there’s a sharp drop-off between these two categories isn’t supported since the 1 percent difference is not statistically significant. In addition, neither the 3.2% nor the 2,2% average growth rates are representative of their debt-to-GDP ratio level categories, since as HAP say just above there’s a wide range of GDP growth performance in all the categories.

So, that does it. That one finding shows that RR did not show that, on average, nations experiencing debt-to-GDP ratios above 90% had negative rates of economic growth, or even that they had an average rate of growth significantly different from the average in the 60 – 90 % category. Given this finding, what happens to the further inference that high debt levels cause lower growth?

In Part One, I showed that even assuming that the R-R finding was correct it still would not have provided any test of the inference that high debt levels cause lower growth. I stated three reasons. First, R-R committed the ecological fallacy in implying that the high level debt category group growth average could be extended to individual nations and times in each group. We can see from the conclusions of HAP, that there was good reason to be concerned about the ecological fallacy because the group growth average was not found to be representative of individual nations and times.

Second, I pointed out that R-R ignored currency regime variables, failing to include them in the analysis, when it is very likely that any association between the debt-to-GDP ratio and economic growth would vary with these variables. Since HAP end up showing that there is only a small difference between averages in the over 90% category and the 60 – 90% category, it is even more likely that including these variables would have washed out the small differences found, or even reversed the relationship claimed by R-R.

Third, I pointed out that control variables that might have shown that the relationship stated by R-R was spurious were not included in the study, so that possible causes of both a high level of debt-to-GDP and economic growth could not be tested. HAP has nothing to say on this score, but it does raise the question of causality and the failure of R-R to analyze it in any rigorous way, and it concludes by questioning the claim that the R-R findings support the view that high levels of debt inevitably cause low growth.

After the Fall Empirical Research

The HAP analysis and the new availability of the R-R data quickly led to three other analyses, all of which began to explore the question of causality, each one by using more rigorous and more sophisticated though not novel techniques of analysis, than used in the study by Reinhart and Rogoff. A question which immediately occurs is why R-R with all the resources they cold call upon didn’t pursue the same or similar analyses either before or after publication of their results in 2010. After all, those replicating their study only a took a few days to begin to explore questions of causality once they had the R-R data set, yet R-R with three years of opportunity or more to do the same or similar analyses of their own data sets, evidently never did anything of the kind. One simply has to ask whether they were afraid of what they would find if they took a deeper dive into their own data.

Dube’s Distributed Lag Cross-country Panel Analysis

The first of the three studies following on HAP was done by Arindrajit Dube in a guest post at Next New Deal entitled “Reinhart/Rogoff and Growth in a Time Before Debt.” Professor Dube is also in the economics department at UMass. Working on 20 OECD nation corrected panel data set of R-R produced by HAP, Dube used LOWESS regressions and distributed lag models. His results speak to the question of whether slow GDP growth causes higher debt-to-GDP ratios, or whether, as R-R opine, while alternately protesting that correlation isn’t causation, higher debt-to-GDP ratios cause relatively low or even negative growth. They suggest that the causation is more likely to run from growth to debt-to-GDP ratios, than from those ratios to growth. Dube also found that 1) any negative relationship between debt ratios and growth is strongest at lower levels of debt, rather than at higher levels as found by R-R, and 2) there is a stronger association between past economic growth, and current debt ratio levels than the association between current debt ratio levels and future economic growth.

Basu’s Time-Series Analysis of the US, Italy and Japan

The second new follow-on to the R-R and HAP studies was done by yet another UMass economics professor, Deepankar Basu and reported at Next New Deal. He addressed the question of causality by examining time series data in Italy, Japan, and the United States, using vector autoregression (VAR) models, accompanied by Granger non-causality tests and impulse response analysis. VAR analysis isn’t enough to determine causality without making additional assumptions about an underlying causal model. But in cases, where one is analyzing a two-variable relationship using time series data and one assumes that causality can only run way or another, or perhaps both ways, the VAR technique can produce evidence about which of the two variables, if any, is prior to the other. I’ll quote Basu’s summary of his results

To summarize, I find that the time series pattern of the dynamic relationship between public debt and economic growth in the postwar U.S., Italian, and Japanese economies is consistent with low growth causing high debt rather than the high debt causing low growth. I draw this conclusion from two types of analyses: Granger non-causality tests and an investigation of impulse response function plots.

Granger non-causality tests allow one to ask the following questions: (a) do debt levels in the past help in better predicting current economic growth, and (b) does economic growth in the past help in improving predictions of current debt levels? The evidence suggests that for the U.S., Italy, and Japan, the answer to the first question is a NO and the answer to the second is a YES.

Impulse response analysis allows one to address the following questions: (a) what is the impact of an unexpected increase in current debt levels on the future time path of economic growth, and (b) how does an unexpected decline in economic growth affect future levels of debt? The data suggests that an unexpected increase in debt levels has only a small effect on future economic growth but an unexpected decline in economic growth is associated with large and long-lasting increases in public debt levels.

So, Basu’s analysis further extends HAP’s suggestion that it’s more likely that growth causes debt than debt causes growth. Like Dube’s it falsifies the austerity conjecture that debt causes growth at least in the context of a two variable model.

Berg and Hartley’s 20 Nation Panel Study

Perhaps the most important of the recent analyses of the R-R data comes from Matthew Berg and Brian Hartley who are Graduate Students in the economics department at the University of Missouri at Kansas City. They followed Dube in analyzing the R-R 20 nation panel data, used and corrected by HAP, using LOWESS regressions, and distributed lag with impulse response analysis.

First, they addressed the important question of whether the relationship between current debt-to-GDP levels and future growth is the same or at least similar across nations. They found (through an examination of individual “backwards/forwards” graphs) that this relationship varied widely across nations. That is, nations were heterogeneous, not homogeneous with respect to this key relationship. They say:

. . . Even if some sort of relationship between debt-to-GDP and growth can in fact be found in cross-country panel analysis, that relationship does not appear to hold up on the level of individual countries. Because economic policy is made on the level of individual countries, this heterogeneity appears to undercut the rationale for any given particular country to make important policy decisions on the basis of government debt-to-GDP ratios.

I’ve italicized their key point in the paragraph for emphasis. Any attempt to generalize across all the 20 nation panel data, such as the R-R attempt to say that a debt-to-GDP ratio above 90% leads to relatively low or negative economic growth contradicts what the data show at the individual nation level for the two key variables, and is therefore just a false inference.

Second, Berg and Hartley also say:

We find that the correlation between government debt-to-GDP ratios and future growth in Reinhart and Rogoff’s . . . dataset results from outliers which come from the country most suggestive of the hypothesis that slow growth causes high levels of government debt – Japan. . . .

That is, the Japanese data disproportionately distort the overall relationship and create a misleading picture, because of the unique history of Japan. But, nevertheless historical examination of both Japan and the other nations provide evidence consistent with the “reverse causation” causation hypothesis that growth causes debt to-GDP ratio levels rather than the alternative hypothesis of a debt-GDP ratio causal ordering priority. Berg and Hartley show this with distributed lag/impulse response analyses and LOWESS regressions with and without the Japanese data. The analysis, for all practical purposes, shows that there is no relationship between current year association between GDP growth and the debt-to-GDP ratio as claimed by R-R.

They also summarize:

. . . This evidence strengthens and reinforces criticisms recently made by Herndon, Ash, and Pollin . . . of research suggesting a negative relationship between government debt-to-GDP ratios and real GDP growth rates. . . . we . . . find evidence suggesting that correlation of government debt-to-GDP ratios and future growth are much more likely explained by “reverse” causation running from slow GDP growth to high government debt-to-GDP ratios than by “forward” causation running from high government debt-to-GDP ratios to slow growth. Furthermore, what little evidence there is for forward causation appears to stem almost entirely from Japanese outliers. Because – as economists generally recognize – Japan is the clearest of all cases of reverse causation, this considerably weakens the argument for forward causation. In addition, we find tremendous heterogeneity on the level of individual countries in the relationship between current government debt-to-GDP ratios and future growth. This suggests that even if substantial evidence for forward causation is eventually discovered in cross-country studies, the effect will likely be small in size and unreliable, and therefore not relevant to economic policy decisions in any particular individual country. Our findings are suggestive, but not conclusive, and more research is needed. We suggest that simultaneous equations models may offer a way forward on the “frontier question” of causality.

Conclusion: You Can’t Generalize Across All Nations and Times About the Impact of the Debt-to-GDP Ratio on Economic Growth

Actually, I think the findings of Berg and Hartley following on and taking into account the findings of HAP, Dube, and Basu are pretty conclusive and not just suggestive. What they say is that the data included in the two-variable analyses flatly contradict the idea that the debt-to-GDP ratio causes economic growth in the individual nations comprising the 20 nation OECD panel. If anything, the evidence is much more consistent with the idea that it is growth that impacts the debt-to-GDP ratio.

I think there has hardly ever been a clearer finding in the Social Sciences than this one. After all, it took HAP, Dube, Basu, and Berg and Hartley only a matter of days to arrive at it. The only way R-R could have missed it is if they weren’t looking for it. It’s as if they just weren’t looking for the truth; but were only looking for an argument that could be used to justify the austerity policies they favored. That’s not economic science. It’s bias, pure and simple.

In Part Three, I’ll end this series on the R-R affair with a retrospective.

(Cross-posted from New Economic Perspectives.)

Make ‘em Prove the Causality Before They Cause Any More Suffering: Part One

3:17 pm in Uncategorized by letsgetitdone

OK, austerity has always been about the causality. The people who are trying their best to get us to cut more and more spending, somewhat less than their best to get us to raise taxes, and who are doing nothing to fix our fraud-laden financial system, or the worst period of dis-employment we’ve experienced since the Great Depression, have been making other people (never themselves) suffer, because they believe the theory that excessive public debt hurts economic growth, and that to get rid of it we must follow a plan of long-term deficit reduction. And I’m being very charitable when I opine that they believe in this theory, because the alternative is that they don’t believe it, but are just using it as an excuse to make other people suffer, and widen the wealth gap between themselves and the rest of the population.

Either way it’s important for the rest of us to demand that before we do anything more based on that theory, they should be forced to prove that it is the best theory out there about the causal relationship between public debt and economy growth. Actually, we should have made them prove that before we allowed Congress and President Obama to start playing austerity games with us way back in 2009 – 2010, because there’s been a lot of water under the bridge since then, including continuing very high disemployment, thousands and thousands of people dying due to lack of health insurance, suicide, depression-related illnesses, crime that need not have occurred, and all the effects of hopelessness that afflict the poor and the middle class during bad economic times. And now, our wonderful leaders have managed to inflict the sequestration upon us, while planning to inflict entitlement cuts on the old and the sick.

Lately, of course, the armor of the austerians, and their claims of empirical support for their view that high levels of the debt-to-GDP ratio are associated with and/or cause very low or even negative rates of economic growth has suffered repeated blows from Economics Graduate Students and Professors at the University of Massachusetts and the University of Missouri at Kansas City, in recent papers. I’ll review those studies in Part Two. In the rest of this part, I’ll evaluate the proof austerians had for their policies before this new research work appeared.

What Proof Did They Have?

So, what proof did they have, before the recent research appeared, that austerity is the best course to follow? Well, it’s been practiced all over Europe for years now, and what are the results? Only record unemployment, shrinking economies, increasing public debt, crime, public unrest, increasing suicide rates, damaged health care systems denying care to people who need them, no improvement to speak of in the economic outlook, and immense dissatisfaction all over the continent.

How about here? A stagnant economy, three steps forward, two steps back, high youth unemployment, no jobs for college graduates, layoffs in the public sector and declining services, low wages, recovery limited to the financial sector and the stock market — the kinds of results that in not so many years will produce a plutocracy, if one doesn’t exist already.

Everywhere austerity is being practiced we see a slowed economy. In some places, like Japan, we see short periods of it followed by some backing off, producing stagnation for close to a quarter of a century. In other places, like Australia and Canada we’ve seen enough of it that the prosperity they could have enjoyed is beyond their grasp.

Sure, Germany, hasn’t hit real hard times yet because their export-led economy gives them more policy space to run surpluses, but most of the nations of the Eurozone can’t run a trade surplus, so for them, continuing government austerity results in private sector losses, year after year, absent a change in rules by the Eurozone. Even the German economy has been slowing as its neighbors can afford less and less German goods, and France is seeing more than 10% unemployment and is rapidly becoming another basket case, creating the need for changing the well known Eurozone acronym to the PFIIGS. Is there an unambiguous success for austerity since the Second World War in a country running a trade deficit? I don’t know of one.

So, what about the work of Carmen Reinhart and Kenneth Rogoff? Didn’t it show that, on average, nations experiencing debt-to-GDP ratios above 90% had negative rates of economic growth? And doesn’t this provide evidence that excessive debt does cause low economic growth and even economic contraction, so that if we value economic growth, we must reduce the debt-to-GDP ratio to a much lower level than 90% before we try to use deficit spending to try again to grow?

Well, the answer to these questions is no, and no. I’ll explain the second “no” first, and consider the first “no” later on in Part Two.

Common Fallacies: First, Reinhart and Rogoff never claimed that the findings of their analysis of their very extensive cross-national, historical database supported causal inference. It’s true that after they wrote their paper and published their book reporting on their data and analysis, they recommended austerity policies and either referred to their work in that context, or have been identified by others hosting an appearance or publishing an article as having done that work to support their “expertise.” So, they talked out of both sides of their mouths; but in their work itself they acknowledge that correlation isn’t causation, and that they hadn’t proved cause and effect. And they urged further research to explore cause-and-effect relationships.

In addition, critics of their work have long emphasized that the reported association between high debt-to-GDP levels and low economic growth for all nations, had nothing to say about cause and effect in individual nations and therefore could not serve as the basis for a fiscal policy of austerity, or for Reinhart and Rogoff’s mere opinions that such a policy, expressed in other contexts should be implemented. One problem is that the association between debt-to-GDP and economic growth at levels of debt-to-GDP above 90% doesn’t apply to every instance in every nation. It’s an average, a mean or a median which is reported.

So, the association is ecological across all instances. It is the well-known ecological fallacy of social science to conclude that it applies to all or even most instances in the high debt-to-GDP category. To go on from there, and then suggest that the association is causally relevant in individual systems, is to compound the ecological fallacy with the correlation is causation fallacy. To do that is just terrible social science.

Currency Regime Variables: Read the rest of this entry →