On the growing labour productivity in Canada

Five years ago we published two papers [1, 2], which introduced a new macroeconomic model explaining the evolution of labour productivity in developed countries. This model is parsimonious and uses only one measured macroeconomic variable as the driving force of the productivity growth – real GDP per capita. Figure 1 is borrowed from our monograph “mecћanomics. Economics as Classical Mechanics” (Figure 3.22) and illustrates the predictive power of the model as applied to Canada. (Due to high volatility of productivity measurements, the measured data set is represented by its 5-year moving average, MA(5)). All coefficients in the model for Canada were obtained empirically, as explained in the papers. 

Considering the model simplicity and the accuracy of data on real GDP and productivity, the prediction of the time history in Canada is excellent. (We would be grateful if the reader could provide us with a reference to a model which gives better predictions.) It is also important that the prediction covers the whole period since 1960 with one deterministic link without any structural breaks.

Practically all mainstream macroeconomic models (e.g. DSGE) are using the notion of shocks to productivity as the key phenomenon explaining all bigger deviations in the rate of real economic growth. This implies that productivity must define real GDP. This assumption contradicts observations, as our model demonstrates – the change in labour force productivity lags by two (!) years behind the defining change in real GDP. Therefore, the labour productivity is not a proactive macroeconomic variable.

 

Figure 1. Observed and predicted productivity in Canada: N(1959)=270000, A₂=$300,

B=-3200000, C=0.108; R²=0.8. (Figure 3.22 in our monograph.)

The original data set was limited to 2007. Six years later, one can test the predictive power of the model using new data. As three years ago, we use the data set published by the Conference Board. Figure 2 shows that our prediction for 2008 through 2012 was accurate. In  2010,  we expected a significant growth in labour productivity in Canada. This growth has been actually observed since 2010 and continues in 2013.  

Conclusion:

The labour productivity in Canada is on a growing trend and will retain the rate of ~1.0% per year in 2013-2016.

Figure 2. Same as in Figure 1 extended by five readings between 2008 and 2012.

 

The rate of unemployment in May below 7.5%?

Today a new estimate will be announced for the rate of unemployment in the USA. We have been following this variable since 2006 when our general model linking labor force, price inflation, and rate of unemployment was first published. Approximately a  month ago we predicted a significant drop in this rate in May 2013 as based on the fall in labor force five years ago (i.e. in 2008). The range of expert predictions for May 2013 in 7.4% to 7.5% as reported by the WSJ Market Data Center.

Our best guess is 7.3% to 7.1% as figure below suggests.

 

Waveform cross correlation for seismic monitoring of underground nuclear explosions. Part II: Synthetic master events

A new working paper is available on arxiv.org This is a link to pdf file.

Abstract

Waveform cross correlation is an efficient tool for detection and characterization of seismic signals. The efficiency critically depends on the availability of master events. For the purposes of the Comprehensive Nuclear-Test-Ban Treaty, cross correlation can globally reduce the threshold monitoring by 0.3 to 0.4 magnitude units. In seismically active regions, the optimal choice of master events is straightforward. There are two approaches to populate the global grid in aseismic areas: the replication of real masters and synthetic seismograms calculated for seismic arrays of the International Monitoring System. Synthetic templates depend on the accuracy of shape and amplitude predictions controlled by focal depth and mechanism, source function, velocity structure and attenuation along the master/station path. As in Part I, we test three focal mechanisms (explosion, thrust fault, and actual Harvard CMT solution for one of the April 11, 2012 Sumatera aftershocks) and two velocity structures (ak135 and CRUST 2.0). Sixteen synthetic master events were distributed over a 1ox1o grid. We built five cross correlation standard event lists (XSEL) and compared detections and events with those built using the real and grand master events as well as with the Reviewed Event Bulletin of the International Data Centre. The XSELs built using the source of explosion and ak135 and the reverse fault with isotropic radiation pattern demonstrate the performance similar to that of the real and grand masters. Therefore, it is possible to cover all aseismic areas with synthetic masters without significant loss in seismic monitoring capabilities based on cross correlation.

Why Gavyn Davies is wrong about employment targeting

Gavyn Davies criticises  the Fed for wrong money policy targeting on unemployment rate, UER,  instead of the rate of employment, E/P. He  is right  that the rate of unemployment does not express well the full  capacity of the economy. However, the rate of employment  is quite different from the UER. Two figures below do show that the UER has been varying around 5% to 7% since 1948. The Fed can claim that monetary policy is effective because UER is always back to 6%. How can they say that they control E/P if it really has a strong secular component. Gavyn puts the Fed in danger to be responsible for that they can not be responsible for. It will never happen if the Fed has a bit of sense. The rate of employment is out of control not only for the Federal Reserve but also for any authority.

 

A fourty-year period of energy price oscillation

Figure 1. The difference between the headline and core CPI (both seasonally adjusted) since 1957.  The V-shape suggests the similarity of the fall and rise paths. One can estimate the next peak extrapolating the current rise by the previous fall (between 1980 and 2000).

Figure 2. The difference between the headline and core CPI. The red curve is an inverse version of the blue curve reduced by -9 and shifted by 19 years ahead.  One can estimate the distance between the peaks in 1981 and 2019 as the period  of long term oscillations, which is approximately 40 years.  

Figure 3. The difference between the energy and core CPI. The red curve is an inverse version of the blue curve reduced by -65. One can estimate the distance between the peaks as the period  of long term oscillations.  The energy price is likely on a downward trend already.

Employment in Canada revisited

Two years ago we presented a parsimonious model describing the evolution of employment/population ratio in Canada.  In essence, this model is a modified Okun’s law since there exists a trade-off between the change in unemployment and employment. Yesterday, we revisited the rate of unemployment in Canada based on a complimentary model and found an extraordinary high fit between predicted and observed curves. (A comprehensive description of both models also extended by examples in other developed countries is presented in our paper “Modeling Unemployment And Employment In Advanced Economies: Okun’S Law With A Structural Break”. )

 

 

Figure 1 compares the change in the rate of employment (the employment/population ratio), de, and the rate of unemployment, du, in Canada. As expected, the change in the rate of unemployment is slightly more volatile (also because of lower accuracy of measurements). We have retrieved all data on unemployment and employment from the U.S. Bureau of Labor Statistics.  

Figure 1. The (negative) change in the rate of employment compared to the change in the rate of unemployment in Canada.  

Two years ago we estimated several models of employment/population ratio, e. For Canada, the best-fit model has been obtained by the least-squares (applied to the cumulative sums):  

de_t = 0.40dlnG_t – 0.67, t<1984
de_t = 0.44dlnG_t – 0.56, t>1983    (1)  

where dlnG_t is the change rate of real GDP per capita at time t. Figure 2 shows the cumulative curves for the time series in (1). We did not fix the initial value in 1971 and obtained it from the regression. There is a structural break near 1984 which is expressed by a slight shift in the slope of the regression line and a 0.11 change in the intercept term. Since the latter term is cumulated over years one can consider this change as a significant one. It makes a 1.1% employment change over 10 years.  The break is needed because of the change to definitions and measurement procedures rather than actual break in the long-run link between e and G. In any case, functional dependence between these two variables stays untouched.  

The employment/population ratio varies between from ~54.5% in 1971 and ~64.1% (!) in 2008. The agreement between the actual and predicted curves in Figure 2 is excellent. We added two readings for 2011 and 2012 which practically coincide. This observation validates our original model and we will continue reporting on the evolution of employment/population ratio in Canada. 

Figure 3 present results of a linear regression with R²=0.88 for the period between 1971 and 2012. The standard error of the model is 0.82% which is chiefly related to the first ten years where measurements were rather crude.

Figure 2. The cumulative curves for the observed and predicted change in the employment/population ratio, de.

Figure 3. Linear regression of the measured and predicted curves in Figure 2.

A fairy tale about the future rate of unemployment in the US

The rate of unemployment, u, was very high (10%) in 2009. It has been often discussed that the fall in this rate is too slow historically. Figure 1 shows the evolution of u since 1980. There were two major peaks in 1982 (10.8%) and 1992 (7.8%). (All rates are seasonally adjusted.) When the troughs preceding the peaks are synchronized all three descending curves look very similar. This observation says that the current fall in u is not different from the previous. It also tells us a fairy story about the near future.  This rate will fall into the second half of the 2010s. Meanwhile, it may fall to 6.0% in 2013 or in the first half of 2014.

It is worth noting that the start troughs before two major peaks in Figure 1 were higher than the end troughs.  If this trend is retained the next trough should be ~4%.

 

Figure 1. The rate of unemployment in the US

 

Figure 2.  Two previous major peaks synchronized with the most recent. The length of fall is approximately 7 years.