Are business cycles stationary fluctuations around a deterministic trend? empirical evidence from 79 developing countries

There is a large literature that tests the univariate time series properties of the real output series following the seminal work of Nelson and Plosser (1982). Whether or not real output is characterized by a unit root process has important implications. A unit root in real output, for instance, is inconsistent with the notion that business cycles are stationary fluctuations around a deterministic trend. In this paper, we investigate the univariate time series properties of real output for 79 developing countries using the conventional augmented Dickey and Fuller (1979) unit root test, the Zivot and Andrews’ (1992) one structural break unit root test, and the Lumsdaine and Papell (1997) two structural breaks unit root test. Our main finding is that, for 40 countries, real output is stationary around a trend. This indicates that business cycles are stationary fluctuations around a deterministic trend for only 51% of the developing countries in our sample.

PANIC in the presence of uncertainty about the deterministic trend

Most macroeconomic and financial panel variables are trending. However, because of the well-known power problem in the presence of incidental trends, many researchers gamble that their unit root test regressions can be ran without such trends, thereby running the risk of obtaining spurious results. This article takes one of the most general and popular panel unit root tests, known as PANIC, and shows how it can be modified to account for the uncertainty regarding the deterministic trend.

Panel cointegration tests with deterministic trends and structural breaks

This paper proposes Lagrange multiplier (LM) based tests for the null hypothesis of no cointegration in panel data. The tests are general enough to allow for heteroskedastic and serially correlated errors, individual specific time trends, and a single structural break
in both the intercept and slope of each regression, which may be located different dates for different individuals. The limiting distributions of the test statistics are derived, and are found to be standard normal and free of nuisance parameters under the null. In
particular, the distributions are found to be invariant not only withrespect to trend and structural break, but also with respect to the presence of stochastic regressors. A small Monte Carlo study is also conducted to investigate the small-sample properties of the tests. The results reveal that the tests have small size distortions and good power even in very small samples.

Are output fluctuations transitory? New evidence from twenty four Chinese provinces

The fact that an occurrence of a unit root in real output is inconsistent with the notion that business cycles are stationary fluctuations around a deterministic trend makes this an important topic for empirical investigation. We examine this issue for 24 Chinese provinces using the recently developed Lagrange multiplier panel unit root test which allows for a structural break. Our main finding is that real gross domestic product (GDP) and real GDP per capita for Chinese provinces are stationary fluctuations around a deterministic trend.

The effect of recursive detrending on panel unit root tests

This paper analyzes the properties of panel unit root tests based on recursively detrended data. The analysis is conducted while allowing for a (potentially) non-linear trend function, which represents a more general consideration than the current state of affairs with (at most) a linear trend. A new test statistic is proposed whose asymptotic behavior under the unit root null hypothesis, and the simplifying assumptions of a polynomial trend and iid errors are shown to be surprisingly simple. Indeed, the test statistic is not only asymptotically independent of the true trend polynomial, but also is in fact unique in that it is independent also of the degree of the fitted polynomial. However, this invariance property does not carry over to the local alternative, under which it is shown that local power is a decreasing function of the trend degree. But while power does decrease, the rate of shrinking of the local alternative is generally constant in the trend degree, which goes against the common belief that the rate of shrinking should be decreasing in the trend degree. The above results are based on simplifying assumptions. To compensate for this lack of generality, a second, robust, test statistic is proposed, whose validity does not require that the trend function is a polynomial or that the errors are iid.

New improved tests for cointegration with structural breaks

This article proposes Lagrange multiplier-based tests for the null hypothesis of no cointegration. The tests are general enough to allow for heteroskedastic and serially correlated errors, deterministic trends, and a structural break of unknown timing in both the intercept and slope. The limiting distributions of the test statistics are derived, and are found to be invariant not only with respect to the trend and structural break, but also with respect to the regressors. A small Monte Carlo study is also conducted to investigate the small-sample properties of the tests. The results reveal that the tests have small size distortions and good power relative to other tests. © 2007 The Authors Journal compilation 2007 Blackwell Publishing Ltd.

An IV test for a unit root in generally trending and correlated panels

This paper proposes an IV-based panel unit root test that is general enough to accommodate general error serial and cross-section dependence, and a potentially nonlinear deterministic trend function. These allowances make the new test one of the most general around. It is also very simple to implement. Indeed, the IV statistic is asymptotically invariant to not only to all nuisance parameters characterizing the dependence of the errors and the true trend function, but also the deterministic specification of the fitted test regression.

Learning how to engage students online in hard times

In a context of financial restraint and enterprising university managers, teacher-researchers have reason to be sceptical about the trend towards online teaching and away from learning for its own sake. This article departs from both economic and technological determinism and turns instead to ideas about technology embedded in social and political institutions. Activity theory offers a useful means of analysing such embeddedness. Its Marxian assumptions about human nature specify a non-deterministic approach to technology. Its dynamic model of the subjects, tools, and objects of activity within a context of rules, a community, and a division of labour helps to specify aspects of the authors process of learning how to use electronic conferencing effectively. A full deployment of activity theory would also analyse the activity of students. Here the evidence comes mainly from the activity of researcher-teachers engaging greater activity among students. The numbers of students involved precludes reliable quantitative analysis but qualitative evidence from students does support conclusions about researcher-teachers learning how to make best use of electronic conferencing.

Global optimisation of neural networks using a deterministic hybrid approach

Selection of the topology of a neural network and correct parameters for the learning algorithm is a tedious task for designing an optimal artificial neural network, which is smaller, faster and with a better generalization performance. In this paper we introduce a recently developed cutting angle method (a deterministic technique) for global optimization of connection weights. Neural networks are initially trained using the cutting angle method and later the learning is fine-tuned (meta-learning) using conventional gradient descent or other optimization techniques. Experiments were carried out on three time series benchmarks and a comparison was done using evolutionary neural networks. Our preliminary experimentation results show that the proposed deterministic approach could provide near optimal results much faster than the evolutionary approach.

Projecting the trend in the Canadian gender wage gap 2001-2031: will an increase in female education acquisition and commitment be enough?

The paper projects the gender wage gap for 25-64 year-olds in Canada over the period 2001-2031. The empirical analysis uses the Survey of Labour and Income Dynamics together with Statistics Canada demographic projections. The methodology combines the population projections with assumptions relating to the evolution of educational attainment in order to first project the future distribution of human capital skills and, based on these projections, the future size of the gender wage gap. The projections suggest continued gender wage convergence produced by changing skills characteristics. However, a substantial pay gap will remain in 2031.

The successful school: a genuine trend or a statistical artifice?

Schools are increasingly being expected to make improvements based on data about students' learning outcomes. Such an expectation implies that principals, teachers and key personnel within systems can read and act upon the data available. There is evidence, however, that many people have poor understanding of statistical information, and that many factors inside and outside the school have an effect on students' outcomes. This study considers one primary school's data from statewide testing programs. Trends across time are considered as a basis for making judgments about the school's performance in improving students' learning outcomes in literacy and numeracy.

Deterministic versus stochastic quantitative microbial Risk Assessment models for wastewater irrigation of food crops

Reuse of wastewater to irrigate food crops is being practiced in many parts of the world and is becoming more commonplace as the competition for, and stresses on, freshwater resources intensify. But there are risks associated with wastewater irrigation, including the possibility of transmission of pathogens causing infectious disease, to both workers in the field and to consumers buying and eating produce irrigated with wastewater. To manage these risks appropriately we need objective and quantitative estimates of them. This is typically achieved through one of two modelling approaches: deterministic or stochastic. Each parameter in a deterministic model is represented by a single value, whereas in stochastic models probability functions are used. Stochastic models are theoretically superior because they account for variability and uncertainty, but they are computationally demanding and not readily accessible to water resource and public health managers. We constructed models to estimate risk of enteric virus infection arising from the consumption of wastewater-irrigated horticultural crops (broccoli, cucumber and lettuce), and compared the resultant levels of risk between the deterministic and stochastic approaches. Several scenarios were tested for each crop, accounting for different concentrations of enteric viruses and different lengths of environmental exposure (i.e. the time between the last irrigation event and harvest, when the viruses are liable to decay or inactivation). In most situations modelled the two approaches yielded similar estimates of risk (within 1 order-of-magnitude). The two methods diverged most markedly, up to around 2 orders-of-magnitude, when there was large uncertainty associated with the estimate of virus concentration and the exposure period was short (1 day). Therefore, in some circumstances deterministic modelling may offer water resource managers a pragmatic alternative to stochastic modelling, but its usefulness as a surrogate will depend upon the level of uncertainty in the model parameters.