This paper surveys recent developments related to the smooth transition autoregressive (STAR) time series model and several of its variants. We put emphasis on new methods for testing for STAR nonlinearity, model evaluation, and forecasting. Several useful extensions of the basic STAR model, which concern multiple regimes, time-varying non-linear properties, and models for vector time series, are also reviewed.

/pdf/smooth-transition-autoregressive-models-a-survey-of-recent-i1e06puzgu.pdf

Smooth transition autoregressive models — a survey of recent developments

Digital currencies have emerged as a new fascinating phenomenon in the financial markets. Recent events on the most popular of the digital currencies – BitCoin – have risen crucial questions about behavior of its exchange rates and they offer a field to study dynamics of the market which consists practically only of speculative traders with no fundamentalists as there is no fundamental value to the currency. In the paper, we connect two phenomena of the latest years – digital currencies, namely BitCoin, and search queries on Google Trends and Wikipedia – and study their relationship. We show that not only are the search queries and the prices connected but there also exists a pronounced asymmetry between the effect of an increased interest in the currency while being above or below its trend value.

/pdf/bitcoin-meets-google-trends-and-wikipedia-quantifying-the-2owooq86ym.pdf

BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era

We propose a new test based on a Fourier series to approximate the unknown form of a nonlinear time-series model. The test has good size and power properties to detect structural breaks, seasonal parameters and random coefficients. Moreover, it has reasonable power to discriminate between nonlinearity in variables and nonlinearity in parameters. We use the test to show that U.S. inflation is appropriately estimated with a time-varying intercept that jumps in the late 1960’s, peaks in the early 1980’s and then begins to decline. German income and consumption data is used to illustrate the ability of the test to suggest the form of the nonlinearity.

/pdf/a-general-test-for-time-dependence-in-parameters-q74b60lmxx.pdf

A General Test for Time Dependence in Parameters

Health care expenditures and GDP: panel data unit root test results

Whether foreign direct investment (FDI) is beneficial to host country growth or not is a question debated since a long time. This paper provides a survey of the literature on FDI, export and growth, and empirically investigates the causal relationship between economic growth, export and FDI for the ten transition European countries (Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovak Republic and Slovenia). The ARDL bounds testing approach is used to investigate the existance of long-run relationship between FDI, export and economic growth for these countries. After detection of cointegratin relationship, the error-correction based Granger causality test is employed to examine the both long-run and short-run causality issues between the variables by using quarterly data from 1994 to 2008. These causality results reveal that there is causal relationship between FDI, export and economic growth in four out of ten countries considered.

Foreign direct investment, export and economic growth: empirical evidence from new eu countries

Time-series-based econometrics

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Time-series-based econometrics