Gold is the only option in the choiceless situation

The gold price phenomenon is in the centre of the current financial and economic turbulence. The role of gold is a miracle for economic and financial gurus who speculate around without any success to explain is in any useful terms. Gold stays above any economic activity and free market rules since it is not really connected to production and consumption. It also cannot play the role of value saving.  Nobody can say why it is growing and when it will start to (free) fall. There is no doubt that the latter event will happen sooner or later.   

Gold is not a normal product or asset. It plays a psychological role inherited from its “golden” past.   I would call the gold rally as the only option in the choiceless situation when everything else is worse. 

Some experts say that gold is a new bubble. In my opinion, it’s right in some sense. However, this bubble, as might be with the previous one, is a game for smart investors who can quickly withdraw money from this Panama affair (remember what happened in 1979-1980). Thus, I would recommend not joining if one cannot withdraw money momentarily when the price will start to fall.

Bernanke on inflation

Our prediction for the 2010s is very low and negative inflation. It has come to Ben as well.

Chairman Ben S. Bernanke  on inflation.

The Outlook for Inflation

Let me turn now from the outlook for growth to the outlook for inflation. Prices of many commodities, notably oil, increased sharply earlier this year. Higher gasoline and food prices translated directly into increased inflation for consumers, and in some cases producers of other goods and services were able to pass through their higher costs to their customers as well. In addition, the global supply disruptions associated with the disaster in Japan put upward pressure on motor vehicle prices. As a result of these influences, inflation picked up significantly; over the first half of this year, the price index for personal consumption expenditures rose at an annual rate of about 3-1/2 percent, compared with an average of less than 1-1/2 percent over the preceding two years.

However, inflation is expected to moderate in the coming quarters as these transitory influences wane. In particular, the prices of oil and many other commodities have either leveled off or have come down from their highs. Meanwhile, the step-up in automobile production should reduce pressure on car prices. Importantly, we see little indication that the higher rate of inflation experienced so far this year has become ingrained in the economy. Longer-term inflation expectations have remained stable according to the indicators we monitor, such as the measure of households' longer-term expectations from the Thompson Reuters/University of Michigan survey, the 10-year inflation projections of professional forecasters, and the five-year-forward measure of inflation compensation derived from yields of inflation-protected Treasury securities. In addition to the stability of longer-term inflation expectations, the substantial amount of resource slack that exists in U.S. labor and product markets should continue to have a moderating influence on inflationary pressures. Notably, because of ongoing weakness in labor demand over the course of the recovery, nominal wage increases have been roughly offset by productivity gains, leaving the level of unit labor costs close to where it had stood at the onset of the recession. Given the large share of labor costs in the production costs of most firms, subdued unit labor costs should be an important restraining influence on inflation.

Krugman on the profession. The reasons economists have failed

Paul Krugman wrote a relatively short article on the economic profession and crisis. The reader can find it here. There is no big difference with many other economists’ claims on the reason behind the overall failure to describe the current crisis. The profession has problems in “social dynamics” and thus should listen Paul and follow his ideas up. The profession needs consolidation around some “right” ideas and “wrong” idea must be avoided.

There is only one good sentence in this paper

“All of this would have been OK if the triumph of anti-Keynesianism was justified by superior empirical success. “

This requirement of the empirical justification must be applied to the profession as a whole. Economics as a profession needs a measurable accountability. Otherwise, there is no rule how to justify and select between various models and predictions. Unfortunately, the economic profession defends its quantitative unaccountability fiercely. As a consequence, economists will fail again, and again, and again … One can bet the failure without any risk.

On some methodical mistakes in the presentation of income inequality

Uwe Reinhardt onEconomix has posted on economic inequality. He presented Figure 1 illustrating the growth in income inequality in the U.S. since 1975. (All original data were taken from the Economic Report of the President to the Congress. These data sets are provided by the US Census Bureau (CB) and the Bureau of Economic Analysis (BEA).)  

Figure 1. 

So, Figure 1 has to prove that the income distribution in the US has been experiencing significant changes since 1975 and the level of economic inequality has increased dramatically.  The problem is that Figure 1, containing the change in real GDP per capita (borrowed from BEA) and the evolution of real median household income (borrowed from CB), does not prove any change in inequality. There are two mistakes. First, one should not mix household and personal incomes in one plot. The structure of households in the US is subject to severe changes. At the same time, real GDP per capita can is related to the smallest possible economic agent and is not subject to changes in structure. Secondly, the deviation between median income and real GDP per capita results not from the change in income inequality but from real economic growth. We demonstrate both effects below.

Figure 2 displays the evolution mean and median personal and household incomes and that of real GDP per capita as reported by the US Census Bureau. One can see that mean and median incomes for both persons and households do deviate since 1975. It is a crucial fact that all data sets in Figure 2, except GDP, are taken from the same source – the Current Population Surveys Annual Social and Economic Supplements conducted every March.  All variables are measured together during the same surveys from the same households. Figure 3 depicts the corresponding estimates of Gini ratio for both personal and household income distribution. It is clear that the personal Gini ratio has been decreasing since 1994 (no CB’s estimates before 1994), while the household Gini ratio has been experiencing a steady growth. Hence, the deviation between mean and median income does not necessarily proves the growth in economic inequality, at least as expressed by the Gini ratio.

Figure 2. The evolution of mean and median personal and household incomes and that of real GDP per capita, all normalized to 1975.

Figure 3. Gini ratio for personal and household income distributions. 

The difference in Gini ratios in Figure 3 also demonstrates the changes in the structure of households.  The distribution of personal incomes practically does not change over time with the Gini ratio slightly falling since 1994. The corresponding households, which consist of the same persons as used in the personal income distribution, does experience tangible changes as expressed by the growth in income inequality. Thus, one must never use real GDP per capita and real median household income in the same plot. These variables are different by nature and their comparison is intrinsically biased.

In turn, the deviation between median personal income and real GDP per capita in Figure 2 does not imply any inequality change, as least as measured by the US Census Bureau.  The mean personal income can be a good proxy to the real GDP per capita. Figure 4 shows the ratio of the GDP per capita and the mean income. This ratio also depends on the difference between the total population used for the GDP per capita estimates and the people with income used for the mean income estimates.

Figure 4. Per capita GDP divided by the mean personal income in Figure 2.  

Oil price in August

In May 2011, we predicted oil (WTI) price to fall to the level of $70 per barrel by the end of 2011.  This is a monthly revision for August 2011. We consider the average oil price of $86 per barrel what is equivalent to the producer price index of 240 in August.  (Actual estimate will be published by the Bureau of Labor Statistics in the middle of September.)

Figure 1 compares our prediction with actual oil price in 2011. In August 2011, the predicted price is a bit higher than the predicted one. However, we still expect the price to fall by approximately $6 per month to the level of ~$70 in December 2011. We also expect the price to slowly fall through 2016 and put the uncertainty bounds for the long-term trend in oil price. The level of oil price in 2016 is between $30 and $60 per barrel. 

Figure 1. Oil price prediction in 2011. The price is expected to fall by $6 per month between June and December 2011. The price level is ~$70 in December 2011. We also show the range of expected price evolution by 2016.

The war in Iraq and the period of volatility

The causality principle does not imply “after means caused” and we do not consider the war in Iraq as the cause of economic volatility in the U.S. and world wide. At the same time, the war in Iraq was the first big war for resources after the USSR disintegration. In 2003, the level of volatility in resource prices jumped and has been very high since then. We illustrate this jump in several figures below.  We present the evolution of relative producer prices, pi, of selected commodities, iPPI. In order to remove the base effect we calculate the deviation from the overall PPI, PPI, and normalize it to the PPI:

pi(t)= (PPI-iPPI)/PPI

where i corresponds to iron&steel, gold ores, crude petroleum (US domestic production). 

A higher volatility is not a surprise for the market but since 2004 is has a coherent driving force behind all commodities. It seems that this force is not an economic one but includes a strong component of new political (military) balance. Libya might be the most recent example.

Cui prodest? Might be speculators but not honest investors and general public.

Halliburton's shares

We have already presented updated pricing models for ConocoPhillips and ExxonMobil as based on the differences between CPI and PPI components. Our share pricing concept was introduced two years ago and predicted share prices for a few energy companies. ConocoPhillips (COP) and Exxon Mobil (XOM) from the S&P 500 list were the biggest and demonstrated almost no difference in the sensitivity to the difference between the core and headline CPIs. Halliburton’s share (HAL) was also modeled showed a dramatically different sensitivity. We made a tentative conclusion that COP and XOM might have a larger return to an investor considering energy stocks.

Basically, we demonstrated that the time history of a share price, p(t), (for example, HAL) could be accurately approximated by a linear function of the difference between the core CPI, cCPI(t), and the headline CPI in the United States. At the initial stage of our research, this difference was found to be the best to predict share prices in the energy subcategory.

Mathematically, a share price, HAL(t), (we use a monthly closing price adjusted for dividends and splits) can be approximated by a linear function of the lagged difference between the core and headline CPI:

HAL(t) = A + BdCPI(t+t₁)                                       (1)

where dCPI(t+t₁)=cCPI(t+t₁)–CPI(t+t₁), A and B are empirical constants. In the original model for HAL for the period between 1999 and 2009, A=43, B=-3.5; t is the elapsed time; and t₁=0 year is the time delay between the share and the CPI change, i.e. the CPI has a lag behind the share price.

In this article, we test several pricing models for Halliburton, HAL(t), with the same CPI and PPI components tested for ConocoPhillips and ExxonMobil. The set of defining indices includes: the core and headline CPI, the consumer price index of energy, eCPI, and the producer price index of crude petroleum, pPPI, together with the overall PPI. Thus, we test model (1) for HAL(t) using two different differences for the period between 2001 and 2011: 

HAL(t) = A1 + B1(cCPI(t) - eCPI(t))  (2)   

HAL(t) = A2 + B2(pPPI(t) - PPI(t))         (3) 

All coefficients in (1)-(3) were estimates by the least squares for the period between January 2001 and July 2011. As for ConocoPhillips and ExxonMobil, we found no time delay between the share price and defining differences, i.e. t₁=0. 

Figures 1 through 3 compare three HAL models. Corresponding coefficients are given in Figure captions. As in our original study, the best model (in sense of RMS residual, s) for the period between 2001 and July 2011 is based on the core and headline CPI (s=$4.18). Almost the same accuracy is associated with the model based on the core and energy CPI (s=$4.44).

At the same time, model (3) based on the producer price indices is the worst (s=$9.31). This may mean that Halliburton does not depend much on the producer price indices. Interestingly, the change in oil price does accurately describe the period of the financial crisis. However, the model fails to predict slow changes in the share price. Currently, the deviation between the observed and predicted prices is $20.

Halliburton’s shares were less sensitive to the change in consumer prices during the financial crisis than those of XOM and COP. However, the overall agreement between the observed and predicted prices is very good for the past ten years. One can expect that the current deviation from the predicted price will disappear in the near future and the observed price will fall down to $40 per share. In the long-run, the expected fall in oil price at a five-year horizon down to $30 per barrel will likely result in a proportional decrease in HAL’s shares.

Figure 1.  The observed HAL price and that predicted from the core and headline CPI.  A=$43, B=-3.4.

Figure 2.  The observed HAL price and that predicted from the core CPI and the consumer price index of energy.  A1=$30, B1=-0.3.

Figure 3.  The observed HAL price and that predicted from the overall PPI and the producer price index of crude petroleum (domestic production).  A2=$25, B2=-0.13.