Category Archives: macroeconomic forecasting

gasoline price forecasts, impacts of offshoring, macroeconomic forecasting

What Up? The Trump Years – I

From the standpoint of business forecasting, Donald Trump is important. His challenge to various conventional wisdoms and apparently settled matters raises questions about where things will go in 2017 and beyond. Furthermore, his style of governance is unknown, since as a businessman and minor celebrity, Trump has literally no government experience. He is an Outsider to the political scene, arriving with a portfolio of ideas like mass deportations of illegal immigrants, a massive wall between the United States and its southern neighbor, Mexico, bringing manufacturing jobs back, no further gun controls, and more rigorous screening of immigrants from the Middle East and Muslim countries.

So, with Donald Trump’s Inauguration January 20, a lot seems up in the air. But behind the hoopla, fundamental economic processes and trends are underway. What types of forecasts, therefore, seem reasonable, defensible?

Some Thoughts on Economics

Let’s start with economics.

Donald Trump could be the President who returns inflation and higher interest rates to the equation.

Offshoring and outsourcing have been factors in creating industrial wastelands and hollowed out production in the US – areas where you can drive for miles through abandoned buildings and decaying business centers. At the same time, offshoring and outsourcing bring low-cost electronics and other products to US consumers.

It is a Faustian bargain. If you were a wage-earner with a high school education (or less), supporting a family working in the “fast food sector” or convenience store, maybe holding two jobs to patch together enough income for bills – what you got was a $500 big screen TV and all sorts of gadgets for your kids. You could buy a cheap computer, and cheap clothing, too. Credit cards are available, although less so after 2008.

Oh yeah, another place you could work is in a Big Box store, whose long aisles and vanishing sakes clerks serve as the terminus of global supply chains coursing through ports on the West and East coasts. These are the ports where box-car size containers from China and elsewhere are unloaded, and put on rail cars or moved by truck to stores where consumers can purchase the goods packed in these containers largely on credit.

Is it even possible to slow, stop, or reverse this dynamic?

Let’s see, the plan for bringing manufacturing back to the United States involves deregulation of business, making doing business in the US more profitable. One idea that has been floated is that deregulation would provide incentives for US business to repatriate all that money they are holding overseas back to the US, where it could be invested in America.

Before taking office, President-elect Trump earned points with his supporters by “jawboning” US and foreign companies to keep jobs here, threatening taxes or fees for re-importing stuff to the US from newly relocated operations.

But most of the returning manufacturing would be highly capital intensive (think”robots”) so that only a few more jobs could be garnered from this re-investment in America, right?

Well, before dismissing the idea, note that some of these new jobs would be good-paying, probably requiring higher skills to run more automated production processes.

But this is a different game – producing in the United States, discouraging companies to move operations abroad to lower cost environments, placing taxes, fees, or tariffs on goods manufactured abroad coming into the US. This also involves higher prices.

There is another thread, though, to do with the impact of “deregulation” on the US oil and gas industry, aka “fracking.”

When American ingenuity developed hydraulic fracturing technology (“fracking”) to tap lower yield oil and gas reserves in areas of Texas, South Dakota, and elsewhere, US oil and gas production surged almost to the point of self-sufficiency. But then the Saudi’s lowered the boom, and oil prices dropped, making the higher cost US wells unprofitable, and slowing their expansion.

Before that happened, however, it was apparent fracking in the West and the older oil fields of the Eastern US energized activity up the supply chain, drawing forth significant manufacturing of pipes and equipment. The proverbial boom towns cropped up in the Dakotas and Texas, where hours of work could be long, and pay was good.

Clearly, as oil prices rise again with various global geopolitical instabilities, the US oil and gas industry can rise again, create large numbers of jobs and, also, significant environmental degradation – unless done with high standards for controlling wastes and methane emissions.

But Mr. Trump nominated the former Oklahoma Attorney General to head the US Environmental Protection Agency (EPA) – an agency which Mr. Trump vowed at one point in the campaign to eliminate and which his nominee Scott Pruitt fought tooth and nail in the courts.

So, concern with the environment to the winds, there is a case for a Trump “boom” in 2017 and 2018 – if global oil prices can stay above the breakeven point for US oil and gas production.

Another thread or storyline ties in here  – deportations and stronger controls over illegal immigration.

Again, we have to consider how things are actually made, and we see that, as Anthony Bourdain has noted, many of the restaurant jobs in New York City and other big cities  – in the kitchen especially – are filled by new migrants, many not here legally.

Also, scores of construction jobs in the Rocky Mountain West are filled by Hispanic workers.

Pressure on these working populations to produce their papers can only lead to higher wages and costs, which will be passed along to consumers.

And don’t forget President Trump’s promise to restore US military preparedness. As “cost-plus” contracts, US defense production acts as a conduit for price increases, and may be overpriced (the alternative being to let potential enemies manufacture US weapons).

So what this thought experiment suggests is that, initially, jobs in the Trump era may be boosted by captive or returning manufacturing operations and resumption of the US oil and gas boom – but be accompanied by higher prices. Higher prices also are thematic to limiting the labor pool in US industries, and the cost-overruns are endemic to US defense production.

This is not the end of the economics story, obviously.

The next thing to consider is the US Federal Reserve Bank, which, under Chairman Yellen and other members of the Board of Governors is itching to increase interest rates, as the US economy recovers.

Witnessing a surge of employment from fracking jobs plus a smatter of repatriation of US manufacturing, and the associated higher prices involved with all of this, the Fed should have plenty of excuse to bring interest rates back to historic levels.

Will this truncate the Trump boom?

And what about international response to these developments in the United States?

applied macroeconomic forecasting methods, Big Data, macroeconomic forecasting

Is the Economy Moving Toward Recession?

Generally, a recession occurs when real, or inflation-adjusted Gross Domestic Product (GDP) shows negative growth for at least two consecutive quarters. But GDP estimates are available only at a lag, so it’s possible for a recession to be underway without confirmation from the national statistics.

Bottom line – go to the US Bureau of Economics Analysis website, click on the “National” tab, and you can get the latest official GDP estimates. Today, (January 25, 2016) this box announces “3rd Quarter 2015 GDP,” and we must wait until January 29th for “advance numbers” on the fourth quarter 2015 – numbers to be revised perhaps twice in two later monthly releases.

This means higher frequency data must be deployed for real-time information about GDP growth. And while there are many places with whole bunches of charts, what we really want is systematic analysis, or nowcasting.

A couple of initiatives at nowcasting US real GDP show that, as of December 2015, a recession is not underway, although the indications are growth is below trend and may be slowing.

This information comes from research departments of the US Federal Reserve Bank – the Chicago Fed National Activity Index (CFNAI) and the Federal Reserve Bank of Atlanta GDPNow model.

CFNAI

The Chicago Fed National Activity Index (CFNAI) for December 2015, released January 22nd, shows an improvement over November. The CFNAI moved –0.22 in December, up from –0.36 in November, and, in the big picture (see below) this number does not signal recession.

FREDCFNAI

The index is a weighted average of 85 existing monthly indicators of national economic activity from four general categories – production and income; employment, unemployment, and hours; personal consumption and housing; and sales, orders, and inventories.

It’s built – with Big Data techniques, incidentally- to have an average value of zero and a standard deviation of one.

Since economic activity trends up over time, generally, the zero for the CFNAI actually indicates growth above trend, while a negative index indicates growth below trend.

Recession levels are lower than the December 2015 number – probably starting around -0.7.

GDPNow Model

The GDPNow Model is developed at the Federal Reserve bank of Atlanta.

On January 20, the GDPNow site announced,

The GDPNow model forecast for real GDP growth (seasonally adjusted annual rate) in the fourth quarter of 2015 is 0.7 percent on January 20, up from 0.6 percent on January 15. The forecasts for fourth quarter real consumer spending growth and real residential investment growth each increased slightly after this morning’s Consumer Price Index release from the U.S. Bureau of Labor Statistics and the report on new residential construction from the U.S. Census Bureau.

The chart accompanying this accouncement shows a somewhat less sanguine possibility – namely that consensus estimates and the output of the GDPNow model have been on a downward trend if you look at things back to September 2015.

GDPNow

business cycle, Federal Reserve policies and impacts, financial forecasting, macroeconomic forecasting

The Interest Rate Conundrum

It’s time to invoke the parable of the fox and the hedgehog. You know – the hedgehog knows one thing, sees the world through the lens of a single commanding idea, while the fox knows many things, entertains diverse, even conflicting points of view.

This is apropos of my reaction to David Stockman’s The Fed’s Painted Itself Into The Most Dangerous Corner In History—–Why There Will Soon Be A Riot In The Casino.

Stockman, former Director of Office of Management and Budget under President Ronald Reagan who later launched into a volatile career in high finance (See https://en.wikipedia.org/wiki/David_Stockman) currently lends his name to and writes for a spicy website called Contra Corner.

Stockman’s “Why There Will Soon Be a Riot in The Casino” pivots on an Op Ed by Lawrence Summers (Preparing for the next recession) as well as the following somewhat incredible chart, apparently developed from IMF data by Contra Corner researchers.

WEOchart

The storyline is that planetary production fell in current dollar terms in 2015. This isn’t because physical output or hours in service dropped, but because of the precipitous drop in commodity prices and the general pattern of deflation.

All this is apropos of the Fed’s coming decision to raise the federal funds rate from the zero bound (really from about 0.25 percent).

The logic is unassailable. As Summers (former US Treasury Secretary, former President of Harvard, and Professor of Economics at Harvard) writes –

U.S. and international experience suggests that once a recovery is mature, the odds that it will end within two years are about half and that it will end in less than three years are over two-thirds. Because normal growth is now below 2 percent rather than near 3 percent, as has been the case historically, the risk may even be greater now. While the risk of recession may seem remote given recent growth, it bears emphasizing that since World War II, no postwar recession has been predicted a year in advance by the Fed, the White House or the consensus forecast.

But

Historical experience suggests that when recession comes it is necessary to cut interest rates by more than 300 basis points. I agree with the market that the Fed likely will not be able to raise rates by 100 basis points a year without threatening to undermine the recovery. But even if this were possible, the chances are very high that recession will come before there is room to cut rates by enough to offset it. The knowledge that this is the case must surely reduce confidence and inhibit demand.

So let me rephrase this, to underline the points.

  1. Every business recovery has a finite length
  2. The current business recovery has gone on longer than most and probably will end within two or three years
  3. The US Federal Reserve, therefore, has a limited time in which to restore the federal funds rate to something like its historically “normal” levels
  4. But this means a rapid acceleration of interest rates over the next two to three years, something which almost inevitably will speed the onset of a business downturn and which could have alarming global implications
  5. Thus, the Fed probably will not be able to restore the federal funds rate – actually the only rate they directly control – to historically normal values
  6. Therefore, Fed tools to combat the next recession will be severely constrained.
  7. Given these facts and suppositions, secondary speculative/financial and other responses can arise which themselves can become major developments to deal with.

Header pic of fox and hedgehog from willpowered.co.

interest rate forecast, Janet Yellen outlook, macroeconomic forecasting

Federal Reserve Plans to Raise Interest Rates

It is widely expected the US Federal Reserve Bank will raise the federal funds rate from its seven-year low below 0.25 percent to maybe 0.50 percent. Then, further increases will bring this key short term rate back in line with its historic profile gradually, depending on the health of the US economy and international factors.

This will probably occur next week at the meeting of the Federal Open Market Committee (FOMC), December 15-16.

Here’s a chart from the excellent St. Louis Federal Reserve data site (FRED) showing how unusual recent years are in terms of this key interest rate.

FedFundsRate2

Shading in the chart indicates periods of recession.

Thus, the federal funds rate – which is the rate charged on overnight loans to banking members of the Federal Reserve system – was pushed to the zero bound as a response to the financial crisis and recession 2008-2009.

A December increase has been discussed by prominent members of the Federal Open Market Committee and, of course, in Janet Yellen’s testimony before the US Congress, December 3.

Yet discussion still considers the balance between ‘doves’ and ‘hawks’ on the FOMC. Next year, apparently, FOMC membership may shift toward more ‘hawks’ in voting positions – bankers who see inflation risks from the current recovery. See, for example, Richard Grossman’s Birdwatching at the Federal Reserve.

How far will interest rates rise? One way to address this is by considering the Fed funds futures contract. Currently, the CME futures data indicate a rise to 1.73% over the next 36 months.

All this seems long overdue, based on historical interest rate levels, but that does not stop some alarmist talk.

BIS Warns The Fed Rate Hike May Unleash The Biggest Dollar Margin Call In History

As a result, our only question for the upcoming Fed rate hike is how long it will take before the Fed, shortly after increasing rates by a modest 25 bps to “prove” to itself if not so much anyone else that the US economy is fine, will be forced to mainline trillions of dollars around the globe via swap lines for the second time in a row as the world experiences the biggest USD margin call in history.

By the end of next week or probably just after the first of 2016, interest rates may move a little from the zero bound, and from then on, one fulcrum of all business and economic forecasts will be the pace of further increases.

fractal market hypothesis, long memory in time series, macroeconomic forecasting, stock market forecasts

Fractal Markets, Fractional Integration, and Long Memory in Financial Time Series – I

The concepts – ‘fractal market hypothesis,’ ‘fractional integration of time series,’ and ‘long memory and persistence in time series’ – are related in terms of their proponents and history.

I’m going to put up ideas, videos, observations, and analysis relating to these concepts over the next several posts, since, more and more, I think they lead to really fundamental things, which, possibly, have not yet been fully explicated.

And there are all sorts of clear connections with practical business and financial forecasting – for example, if macroeconomic or financial time series have “long memory,” why isn’t this characteristic being exploited in applied forecasting contexts?

And, since it is Friday, here are a couple of relevant videos to start the ball rolling.

Benoit Mandelbrot, maverick mathematician and discoverer of ‘fractals,’ stands at the crossroads in the 1970’s, contributing or suggesting many of the concepts still being intensively researched.

In economics, business, and finance, the self-similarity at all scales idea is trimmed in various ways, since none of the relevant time series are infinitely divisible.

A lot of energy has gone into following Mandelbrot suggestions on the estimation of Hurst exponents for stock market returns.

This YouTube by a Parallax Financial in Redmond, WA gives you a good flavor of how Hurst exponents are being used in technical analysis. Later, I will put up materials on the econometrics involved.

Blog posts are a really good way to get into this material, by the way. There is a kind of formalism – such as all the stuff in time series about backward shift operators and conventional Box-Jenkins – which is necessary to get into the discussion. And the analytics are by no means standardized yet.

Federal Reserve policies and impacts, financial forecasting, forecasting turning points, macroeconomic forecasting

Coming Attractions

Well, I have been doing a deep dive into financial modeling, but I want to get back to blogging more often. It gets in your blood, and really helps explore complex ideas.

So- one coming attraction here is going to be deeper discussion of the fractal market hypothesis.

Ladislav Kristoufek writes in a fascinating analysis (Fractal Markets Hypothesis and the Global Financial Crisis:Scaling, Investment Horizons and Liquidity) that,

“..it is known that capital markets comprise of various investors with very different investment horizons { from algorithmically-based market makers with the investment horizon of fractions of a second, through noise traders with the horizon of several minutes, technical traders with the horizons of days and weeks, and fundamental analysts with the monthly horizons to pension funds with the horizons of several years. For each of these groups, the information has different value and is treated variously. Moreover, each group has its own trading rules and strategies, while for one group the information can mean severe losses, for the other, it can be taken a profitable opportunity.”

The mathematician and discoverer of fractals Mandelbrot and investor Peters started the ball rolling, but the idea maybe seemed like a fad of the 1980’s and 1990s.

But, more and more,  new work in this area (as well as my personal research) points to the fact that the fractal market hypothesis is vitally important.

Forget chaos theory, but do notice the power laws.

The latest  fractal market research is rich in mathematics – especially wavelets, which figure in forecasting, but which I have not spent much time discussing here.

There is some beautiful stuff produced in connection with wavelet analysis.

For example, here is a construction from a wavelet analysis of the NASDAQ from another paper by Kristoufek

Wavlet1

The idea is that around 2008, for example, investing horizons collapsed, with long term traders exiting and trading becoming more and more short term. This is associated with problems of liquidity – a concept in the fractal market hypothesis, but almost completely absent from many versions of the so-called “efficient market hypothesis.”

Now, maybe like some physicists, I am open to the discovery of deep keys to phenomena which open doors of interpretation across broad areas of life.

Another coming attraction will be further discussion of forward information on turning points in markets and the business cycle generally.

The current economic expansion is growing long in tooth, pushing towards the upper historically observed lengths of business expansions in the United States.

The basic facts are there for anyone to notice, and almost sound like a litany of complaints about how the last crisis in 2008-2009 was mishandled. But China is decelerating, and the emerging economies do not seem positioned to make up the global growth gap, as in 2008-2009. Interest rates still bounce along the zero bound. With signs of deteriorating markets and employment conditions, the Fed may never find the right time to raise short term rates – or if they plunge ahead will garner virulent outcry. Financial institutions are even larger and more concentrated now than before 2008, so “too big to fail” can be a future theme again.

What is the best panel of financial and macroeconomic data to watch the developments in the business cycle now?

So those are a couple of topics to be discussed in posts here in the future.

And, of course, politics, including geopolitics will probably intervene at various points.

Initially, I started this blog to explore issues I encountered in real-time business forecasting.

But I have wide-ranging interests – being more of a fox than a hedgehog in terms of Nate Silver’s intellectual classification.

I’m a hybrid in terms of my skill set. I’m seriously interested in mathematics and things mathematical. I maybe have a knack for picking through long mathematical arguments to grab the key points. I had a moment of apparent prodigy late in my undergrad college career, when I took graduate math courses and got straight A’s and even A+ scores on final exams and the like.

Mathematics is time consuming, and I’ve broadened my interests into economics and global developments, working around 2002-2005 partly in China.

As a trivia note,  my parents were immigrants to the US from Great Britain , where their families were in some respects connected to the British Empire that more or less vanished after World War II and, in my father’s case, to the Bank of England. But I grew up in what is known as “the West” (Colorado, not California, interestingly), where I became a sort of British cowboy and subsequently, hopefully, have continued to mature in terms of attitudes and understanding.

applied macroeconomic forecasting methods, macroeconomic forecasting

Economic Impact Modeling

I had a chance, recently, to watch computer simulations and interact with a regional economic impact model called REMI. This is a multi-equation model of some vintage (dating back the 1980’s) that has continued to evolve. It’s probably currently the leader in the field and has seen recent application to assessing proposals for increasing the minimum wage – in California, Vermont, San Francisco – and to evaluating  a carbon tax for the Citizen’s Climate Initiative  (see the video presentation at the end of this post).

One way to interact with REMI is to click on blocks in a computer screen based on the following schematic

REMIblocs

I watched Brian Lewandowski do this at Colorado University’s Leeds School of Business.

Brian set parameters for increases in labor productivity for professional services and changes in investment in primary and secondary educational by clicking on boxes or blocks. Brian, Richard Wobbekind (pictured below), and I discussed results, and how REMI is helpful in exploring “what-if’s” and might have applications to  optimizing tax policies at the state level..

RichWobbekind

Wobbekind is himself a leader in preparing and presenting State-level forecasts for Colorado, and is active in the International Institute of Forecasters (IIF) which sponsors the International Journal of Forecasting and Foresight – as well as being an Associate Dean of CU’s Leeds School of Business.

Key Point About Multi-Equation, Multivariate Economic Models

From the standpoint of forecasting, the best way I can understand where REMI should be placed in the tool-kit is to remember the distinction between conditional and unconditional forecasts.

REMI model documentation indicates that,

The REMI model consists of thousands of simultaneous equations with a structure that is relatively straightforward. The exact number of equations used varies depending on the extent of industry, demographic, demand, and other detail in the specific model being used. The overall structure of the model can be summarized in five major blocks: (1) Output, (2) Labor and Capital Demand, (3) Population and Labor Supply, (4) Wages, Prices, and Costs, and (5) Market Shares

So you might have equations such as,

X1t = a0 + a1Z1t +..+ akZkt

X2t = b0 + b1Z1t +..+ brZrt

In order to predict unconditionally what (X1t,X2t) will be at some specific future time T*, it is necessary to correctly derive the parameters (a0,a1,..,ak,b0,b1,,…,br).

And it also is necessary, for an unconditional forecast, to predict the future values of all the exogenous variables on the right-hand side of the equation – that is all the Z variables that are not in fact X variables.

This usually means that unconditional forecasts from multivariate forecast models have wide and rapidly diverging confidence intervals.

Thus, if you try to forecast future employment in, say, California with such models, they may underperform simpler, single equation models – such as those based on exponential smoothing, for example.

This does not invalidate general systems models such as REMI.

Assuming the flows and linkages of sectors and blocks are realistic and correctly modeled, such models can help think through the consequences of policy decisions, new legislation, and infrastructure investments.

This is essentially to say that these models may present good conditional forecasts – basically “what-if’s” without being the best forecasting tool available.

Here is a video presentation based on the Citizen’s Climate Initiative application of REMI to assessing a carbon tax – an interesting proposal.

applied macroeconomic forecasting methods, Deep Questions, macroeconomic forecasting

Failures of Forecasting in the Greek Crisis

The resounding “No” vote today (Sunday, July 5) by Greeks vis a vis new austerity proposals of the European Commission and European Central Bank (ECB) is pivotal. The immediate task at hand this week is how to avoid or manage financial contagion and whether and how to prop up the Greek banking system to avoid complete collapse of the Greek economy.

Greekvote

Thousands celebrate Greece’s ‘No’ vote despite uncertainty ahead

Greece or, more formally, the Hellenic Republic, is a nation of about 11 million – maybe 2 percent of the population of the European Union (about 500 million). The country has a significance out of proportion to its size as an icon of many of the ideas of western civilization – such as “democracy” and “philosophy.”

But, if we can abstract momentarily from the human suffering involved, Greek developments have everything to do with practical and technical issues in forecasting and economic policy. Indeed, with real failures of applied macroeconomic forecasting since 2010.

Fiscal Multipliers

What is the percent reduction in GDP growth that is likely to be associated with reductions in government spending? This type of question is handled in the macroeconomic forecasting workshops – at the International Monetary Fund (IMF), the ECB, German, French, Italian, and US government agencies, and so forth – through basically simple operations with fiscal multipliers.

The Greek government had been spending beyond its means for years, both before joining the EU in 2001 and after systematically masking these facts with misleading and, in some cases, patently false accounting.

Then, to quote the New York Times,

Greece became the epicenter of Europe’s debt crisis after Wall Street imploded in 2008. With global financial markets still reeling, Greece announced in October 2009 that it had been understating its deficit figures for years, raising alarms about the soundness of Greek finances. Suddenly, Greece was shut out from borrowing in the financial markets. By the spring of 2010, it was veering toward bankruptcy, which threatened to set off a new financial crisis. To avert calamity, the so-called troika — the International Monetary Fund, the European Central Bank and the European Commission — issued the first of two international bailouts for Greece, which would eventually total more than 240 billion euros, or about $264 billion at today’s exchange rates. The bailouts came with conditions. Lenders imposed harsh austerity terms, requiring deep budget cuts and steep tax increases. They also required Greece to overhaul its economy by streamlining the government, ending tax evasion and making Greece an easier place to do business.…

The money was supposed to buy Greece time to stabilize its finances and quell market fears that the euro union itself could break up. While it has helped, Greece’s economic problems haven’t gone away. The economy has shrunk by a quarter in five years, and unemployment is above 25 percent.

In short, the austerity policies imposed by the “Troika” – the ECB, the European Commission, and the IMF – proved counter-productive. Designed to release funds to repay creditors by reducing government deficits, insistence on sharp reductions in Greek spending while the nation was still reeling from the global financial crisis led to even sharper reductions in Greek production and output – and thus tax revenues declined faster than spending.

Or, to put this in more technical language, policy analysts made assumptions about fiscal multipliers which simply were not borne out by actual developments. They assumed fiscal multipliers on the order of 0.5, when, in fact, recent meta-studies suggest they can be significantly greater than 1 in magnitude and that multipliers for direct transfer payments under strapped economic conditions grow by multiples of their value under normal circumstances.

Problems with fiscal multipliers used in estimating policy impacts were recognized some time ago – see for example Growth Forecast Errors and Fiscal Multipliers the IMF Working Paper authored by Oliver Blanchard in 2013.

Also, Simon Wren-Lewis, from Oxford University, highlights the IMF recognition that they “got the multipliers wrong” in his post How a Greek drama became a global tragedy from mid-2013.

However, at the negotiating table with the Greeks, and especially with their new, Left-wing government, the niceties of amending assumptions about fiscal multipliers were lost on the hard bargaining that has taken place.

Again, Wren-Lewis is interesting in his Greece and the political capture of the IMF. The creditors were allowed to demand more and sterner austerity measures, as well as fulfillment of past demands which now seem institutionally impossible – prior to any debt restructuring.

IMF Calls for 50 Billion in New Loans and Debt Restructuring for Greece

Just before to the Greek vote, on July 2, the IMF released a “Preliminary Draft Debt Sustainability Analysis.”

This clearly states Greek debt is not sustainable, given the institutional realities in Greece and deterioration of Greek economic and financial indicators, and calls for immediate debt restructuring, as well as additional funds ($50 billion) to shore up the Greek banks and economy.

There is a report that Europeans tried to block IMF debt report on Greece, viewing it as too supportive of the Greek government position and a “NO” vote on today’s referendum.

The IMF document considers that,

If grace periods and maturities on existing European loans are doubled and if new financing is provided for the next few years on similar concessional terms, debt can be deemed to be sustainable with high probability. Underpinning this assessment is the following: (i) more plausible assumptions—given persistent underperformance—than in the past reviews for the primary surplus targets, growth rates, privatization proceeds, and interest rates, all of which reduce the downside risk embedded in previous analyses. This still leads to gross financing needs under the baseline not only below 15 percent of GDP but at the same levels as at the last review; and (ii) delivery of debt relief that to date have been promises but are assumed to materialize in this analysis.

Some may view this analysis from a presumed moral high ground – fixating on the fact that Greeks proved tricky about garnering debt and profligate in spending in the previous decade.

But, unless decision-makers are intent upon simply punishing Greece, at risk of triggering financial crisis, it seems in the best interests of everyone to consider how best to proceed from this point forward.

And the idea of cutting spending and increasing taxes during an economic downturn and its continuing aftermath should be put to rest as another crackpot idea whose time has passed.

Chinese economy, global business forecasts, macroeconomic forecasting

Video Friday

Here are some short takes on topics of the day related to the economic outlook for the rest of 2015, nationally and globally.

First a couple of videos on the poor performance of the US economy in the first quarter 2015, when real GDP contracted slightly. This also happened last year, and so there may be a rebound, and, of course, the estimates are released at a significant lag – so we won’t know for a while.

US economy shrank in the first quarter of 2015

U.S. Economy Shrank in First Quarter

Then, a couple of videos on the Chinese stock market crash and condition of the Chinese economy – worrisome since China plays a bigger and bigger role in global business. Bear with the halting English in the first video; there is a payoff in terms of a look from the inside. The second is from a couple of months ago, but is extremely informative vis a vis the big picture.

Stock market of China Falls 16, June 2015

China’s Economy: The Numbers Look Scary

And finally Greece.

Greek crisis in 90 seconds | FT Markets

In closing, I have a comments on technical forecasting issues suggested by the above.

First, “nowcasting” with mixed frequency data should always be applied to these prognostications of what will happen to past economic growth, e.g. the 2nd quarter of 2015. My sense is this is not being done widely, but it’s easy to show its efficacy. There is no reason to drawl on about imponderables, when you can just apply available weekly and monthly data, maybe using MIDAS, to get a better idea of what number we are likely see for the 2nd quarter 2015.

Secondly, I doubt data analytics can provide much light on the situation in China, precisely because there is a lot of evidence the data being announced are suspect. You can go too far in claiming this, but there are warning signs about Chinese data these days. It’s probably comparable to assessing the integrity of Chinese company financials – which see very creative accounting. in certain cases.

As far as Greece goes, I think the outcome is completely unpredictable. Greece is a small economy. If turning Greece away means catastrophic consequences, assistance should be forthcoming, and there are resources available for the size of the problem.  Events, however, may have moved beyond rationality.

The crux of the matter seems to be that there needs to be a way to recirculate funds from the surplus exporters (Germany, largely) to the deficit importers (peripheral Europe).

One proposal is for Germany to create a kind of “New Deal” to invest in the European periphery, so that down the line, their economies can become more balanced and competitive. Another approach, which seems to be that of the Christian Democratic Union (CDU) of Germany, is the neoliberal “solution.” Essentially, force wages and living standards down in debtor countries to the point where they again become globally competitive.

European economy, financial forecasts, macroeconomic forecasting

The Greek Conundrum

I’ve been focused on stock price forecast models, recently, and before that, on dynamics of oil prices.

However, it’s clear that almost any global market these days can be affected by developments in Europe.

There’s an excellent backgrounder to the crisis over restructuring Greek debt. See Greece, Its International Competitors and the Euro by the Turkish financial analyst T. Sabri Öncü – a PDF from the Economic and Political Weekly, an Indian Journal.

According to Öncü, the Greeks got in trouble with loans to finance consumption and nonproductive spending, when and after they joined the Eurozone in 2001. The extent of the problem was masked by accounting smoke and mirrors, only being revealed in 2009. Since then “bailouts” from European banking authorities have been designed to insure steady repayment of this debt to German and French banks, among others, although some Greek financial parties have benefited also.

Still, as Öncü writes,

Fast forward to today, despite two bailouts and adjustment programmes Greece has been in depression since the beginning of 2009. The Greece’s GDP is down about 25% from its peak in 2008, unemployment is at about 25%, youth unemployment is above 50%, Greece’s public debt to GDP ratio is at about a mind-boggling 175% and many Greeks are lining up for soup in front of soup kitchens reminiscent of the soup kitchens of the Great Depression of 1929.

As this post is written, negotiations between the new Syrizia government and European authorities have broken down, but here is an interesting video outlining the opposing positions, to an extent, prior to Monday.

Bruegel’s Interview: Debt Restructuring & Greece

Austerity is on the line here, since it seems clear Greece can never repay its debts as currently scheduled, even with imposing further privations on the Greek population.