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This paper illustrates the power of modern statistical modelling in understanding processes characterised by data that are skewed and have heavy tails. Our particular substantive problem concerns film box-office revenues. We are able to show that traditional modelling techniques based on the Pareto-Levy-Mandelbrot distribution led to what is actually a poorly supported conclusion that these data have infinite variance. This in turn led to the dominant paradigm of the movie business that 'nobody knows anything' and hence that box-office revenues cannot be predicted. Using the Box-Cox power exponential distribution within the generalized additive models for location, scale and shape framework, we are able to model box-office revenues and develop probabilistic statements about revenues.

A discussion on the relative merits of quantile, expectile and GAMLSS regression models is given. We contrast the ‘complete distribution models’ provided by GAMLSS to the ‘distribution free models’ provided by quantile (and expectile) regression. We argue that in general, a flexibility parametric distribution assumption has several advantages allowing possible focusing on specific aspects of the data, model comparison and model diagnostics. A new method for concentrating only on the tail of the distributions is suggested combining quantile regression and GAMLSS.

Current macro-econometric models mostly incorporate just two factors of production, labor and capital (with a time-dependent multiplier representing technological change or total factor productivity). These models assume that energy is an intermediate product of some combination of human labor and capital. These models also assume that the supply of energy is driven by economic demand. We assume the contrary, i.e. that useful energy is a primary input, derived (mostly) from natural capital. This failure to capture the impact of primary resources (as useful energy) on economic growth leads to inappropriate formulation of economic growth theories. To understand that impact better we need explicit evidence of marginal products of capital, labor and useful energy or useful work. As applied to the explanation of the past half century of economic growth of the EU-15 countries, the new results demonstrate the use of non-parametric relationships between capital, labor and useful energy to explain economic growth. They also indicate that marginal products of capital, labor and useful energy are variablethe marginal product depends on the levels of capital stock, labor input and useful energy flows. The proposed semi-parametric production function suggests country-specific policy implications for the EU (and other countries).

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