Разработана модель общего макроэкономического равновесия, учитывающая неоднородность экономических агентов и влияние государственных расходов на темпы...

Konchitchki and Patatoukas (2014) (hereafter KP 2014) show that aggregate accounting earnings growth predicts future nominal Gross Domestic Product (GDP) growth and that professional macro forecasters do not fully incorporate the information contained in aggregate accounting earnings. Based on...

This paper examines the cointegrating relationships between UK quarterly stock prices, stock price fundamentals, GDP and consumption. Evidence reported supports cointegration between these four-variables, with results indicating three cointegrating vectors, or a single common stochastic trend....

Monetary policy is hard. In the best of times, it requires a well-informed understanding of the economy and the ability to respond in a timely manner. In less favorable conditions, monetary policy requires near omniscience and the herculean power to stop economic disasters from unfolding.This...

Macroeconomic analysts have been found to not take full account of aggregate accounting earnings when forecasting future growth in U.S. gross domestic product (GDP). Using Australian data, we confirm this finding and find that the association between aggregate earnings and GDP growth is robust...

We examine whether earnings announcement textual tone, aggregated across individual publicly traded firms, helps to predict future GDP growth. Prior literature shows changes in aggregate accounting earnings are useful in predicting future economic growth, but only when aggregate earnings changes...

We document that aggregate accounting earnings growth is an incrementally significant leading indicator of growth in nominal Gross Domestic Product (GDP). Professional macro forecasters, however, do not fully incorporate the predictive content embedded in publicly available accounting earnings...

The data mining technique of time series clustering is well established in many fields. However, as an unsupervised learning method, it requires making choices that are nontrivially influenced by the nature of the data involved. The aim of this paper is to verify usefulness of the time series...

There is growing literature in macroeconomics, especially on business cycle synchronization, employing different methods of time series clustering. However, even as an unsupervised learning method, this technique requires making choices that are nontrivially influenced by the nature of the data...

This paper considers a non-stationary dynamic factor model for large datasets to disentangle long-run from short-run co-movements. We first propose a new Quasi Maximum Likelihood estimator of the model based on the Kalman Smoother and the Expectation Maximisation algorithm. The asymptotic...