This paper studies convergence in per-capita GDP across European regions over the period 1980-2000. We use median unbiased estimators of the rate of convergence to the steady-state growth path, while allowing for unrestricted patterns of heterogeneity and spatial correlation across regions. By...

In machine learning and data science literature, clustering is the task of dividing the observations (data points) into several categories in such a way that data points falling into one group are being dissimilar than the data points falling to the other groups such that the variation within a...

In this paper an approach for automatic detection of segments where a regression model significantly underperforms and for detecting segments with systematically under- or overestimated prediction is introduced. This segmentational approach is applicable to various expert systems including, but...

Non-classical measurement error with false positives and negatives produces biased and inconsistent estimates. This is the case whether the mismeasured variable is a dependent or an explanatory variable. Moreover, having an IV does not fix this issue. Instead, this paper shows that proper...

This research identifies the presence of long memory given return series of the stock markets in the ASEAN-4 countries, namely, Indonesia, Malaysia, the Philippines and Thailand. Daily stock prices from 1994 to 2004, which were neither adjusted for dividends nor inflation, were employed in the...

In machine learning and data science literature, clustering is the task of dividing the observations (data points) into several categories in such a way that data points falling into one group are being dissimilar than the data points falling to the other groups such that the variation within a...

For a weighted sum of asset returns that are independent and identically distributed (IID) up to variance, we derive expressions linking the distribution of variance across assets with higher-order portfolio moments, assuming these quantities are finite. In particular, we show concise...

The task of statistically analysing and understanding high-dimensional financial data sets is one that is increasingly pertinent in an age of burgeoning information. With high frequency measurements and a global investment universe of hundreds of thousands of securities, reducing the dimension...

Diversification is a fundamental topic for all investors but there remains little agreement on how to measure it. Often it is defined ambiguously through risk-based portfolio construction techniques. Recently it has been suggested to connect maximising diversification with minimising risk...