Week 52

I can't believe that it has been a whole year since the groundbreaking.  This is what it looked like one year ago.  Maybe you can see yourself in the pictures?

This is what it looks like today.  I hope it won't be another year until the dedication.

This little anemometer on top of the crane boom is what delayed the installation of Moroni - actually it was the wind as measured by the anemometer

A subcontractor has been insulating the interior for a few weeks with spray on foam

The North parking structure is progressing well

West entrance

Back filling around the South parking structure

The clouds were beautiful right at twilight

This truck has the 2 components that are mixed to make the spray on urethane insulation

More spray on insulation

One of the insulation subcontractors

The other insulation subcontractor

The clouds were perfect!

Employment in Canada

There is a trade-off between the change in unemployment and employment. 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 more volatile. 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.  

In one our previous posts we have estimated Okun’s law for Canada. It is instructive to estimate a model similar to Okun’s law for the 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 – 0.70, t<1984

de_t = 0.56dlnG_t – 0.76, 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). There is a structural break near 1984 which is expressed by a significant shift in slope and a minor change in intercept.  The employment/population ratio varies between from ~54.5% in 1971 and ~64.1% (!) in 2008. The agreement is very good. Figure 3 present results of a linear regression with R²=0.84 for the period between 1971 and 2010.

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.

Employment in the United Kingdom

There is a trade-off between the change in unemployment and employment. Figure 1 compares the change in the rate of employment (the employment/population ratio), de, and the rate of unemployment, du, in the United Kingdom. As expected, the change in the rate of unemployment is more volatile. 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 the UK.

 In our previous post we have estimated Okun’s law for the UK. It is instructive to estimate a model similar to Okun’s law for the employment/population ratio, e. For the UK, the best-fit model has been obtained by the least-squares (applied to the cumulative sums):

de_t = 0.41dlnG_t-1 – 1.11, t<1983

de_t = 0.41dlnG_t-1 – 0.81, t>1982     (1)  

where dlnG_t-1 is the change rate of real GDP per capita one year before, i.e. the predicted curve leads by one year. Figure 2 shows the cumulative curves for the time series in (1). There is a structural break near 1982 which is expressed by a significant shift in intercept without any change in slope.  The employment/population ratio varies around 58% between from ~54.3% in 1982 and ~61% in 1972. There is a dramatic deviation from the measured employment/population ratio after 2008.  This deviation is consistent with the difference for the same years in 2009. Figure 3 present results of linear regression with R²=0.89 for the period between 1972 and 2009.

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.