Stationarity Behaviour Research Articles

Forecasting of Inland Fish Production: Case of Catla (<em>Catla catla</em>) and Gift Tilapia (<em>Oreochromis niloticus</em>) Production in Udawalawa Reservoir in Sabaragamuwa Province, Sri Lanka

This study focused on assessing and forecasting Catla (Catla catla) and Tilapia (Oreochromis niloticus) production in the Udawalawe reservoir in Sri Lanka using an 11-year time series data from 2010 to 2021. The relevant secondary data were collected from the National Aquaculture Development Authority of Sri Lanka (NAQDA). Unit root tests, Dickey-Fuller tests, and Seasonal Auto Regressive Integrated Moving Average (SARIMA) models and trend analysis were applied for the data analyses. According to the results, stationarity behaviour was observed in both Catla and Tilapia production information series. Hence, SARIMA (2,2,1) (1,0,1)12 is the appropriate empirical model for forecasting Catla production. Furthermore, the maximum average landings of Catla production were observed in the March-June time period. SARIMA (1,0,1) (1,1,1)12 was indicated as the most suitable model to forecast Tilapia production in the reservoir. The maximum average of Tilapia production was also observed in the March-June period. Both the SARIMA model and trend analysis gave approximately equal production information regarding Catla and Tilapia. Thus, these findings showed that the SARIMA model has more accuracy than trend analysis when analysing the time series information for short durations. However, when the duration becomes larger, forecasting is not suitable using the SARIMA model, and trend analysis gives a clear view up to a certain level. Both Catla and Tilapia production exhibited significant changing patterns and multiple seasonalities. Thus, trend analysis gives valuable insights than SARIMA model in long term predictions in case of this study. These findings are highly important for enhancing fish production in this reservoir, as they predict future fish catches under the current reservoir conditions.

Integrative stochastic model standardization with genetic algorithm for rainfall pattern forecasting in tropical and semi-arid environments

ABSTRACT Climate patterns, including rainfall prediction, is one of the most complex problems for hydrologist. It is inherited by its natural and stochastic phenomena. In this study, a new approach for rainfall time series forecasting is introduced based on the integration of three stochastic modelling methods, including the seasonal differencing, seasonal standardization and spectral analysis, associated with the genetic algorithm (GA). This approach is specially tailored to eradicate the periodic pattern effects notable on the rainfall time series stationarity behaviour. Two different climates are selected to evaluate the proposed methodology, in tropical and semi-arid regions (Malaysia and Iraq). The results show that the predictive model registered an acceptable result for the forecasting of rainfall for both the investigated regions. The attained determination coefficient (R 2) for the investigated stations was approx. 0.91, 0.90 and 0.089 for Mosul, Baghdad and Basrah (Iraq), and 0.80, 0.87 and 0.94 for Selangor, Negeri Sembilan and Johor (Malaysia).

Stationarity Diagnostics using Functional Expansion Tallies

A methodology for determining fission source stationarity is presented that characterizes the behavior of higher order spatial moments of the fission source distribution using Functional Expansional Tallies (FET’s). The computation of these FET’s does not require a meshing scheme like traditional methods do (e.g Shannon entropy), and is computed natively within the Monte Carlo tallying routine. To determine the efficacy of this new diagnostic, stationarity behavior is analyzed for a variety of one-dimensional and two-dimensional test cases that mimic typical reactor problems. For most problems, the results from an FET-based approach are in close agreement with those from an entropy-based approach. However, for more realistic reactor configurations with higher dimensionality and strong asymmetries, a stationary fission source distribution is better predicted using an FET-based approach.

TTESTING ABSOLUTE PPP HYPOTHESIS FOR TWENTY COUNTRIES THROUGH THE SKELETON FROM A SETAR MODEL: SOME NEW EVIDENCE

In this study, the long run PPP hypothesis was tested considering real effective exchange rate dataset for twenty countries provided by the International Monetary Fund (IMF). By focusing on a nonlinear approach, the study tests IMF monthly dataset for specific nonlinearity. Additionally, the study presents a method to estimate the value that real exchange rate may converge in the long run. Linear and nonlinear cases were distinguished by the Hansen’s test. The Self-Exciting Threshold Autoregressive (Setar) model was applied to estimate potential thresholds to indicate the states turning points of the countries competitiveness. Results suggest that real exchange rate for thirteen countries are highly nonlinear and subjected to regime switching. The asymptotic stability analysis guarantees the data stationarity behavior. Absolute PPP hypothesis was supported in five out of thirteen cases. In these few cases the real exchange rate converges to a stable equilibrium not far from the value predicted by the PPP hypothesis.

The persistence in real interest rates: Does it solve the intertemporal consumption behavior puzzle?

This paper investigates the stationarity behavior of the ex-post real interest rates (RIRs) for 12 Asian countries. Formal tests conducted indicate that high persistence is an intrinsic characteristic in the majority of the RIRs. We consider local-persistent model to assess the degree of persistence in these series. The findings from this devise reveal that RIRs are persistent, but are characterized by a mean-reverting process. The consistency of the persistence comparable amongst the series is confirmed after accounting for the volatility of the consumption growth. Applying a test proposed by Leybourne et al. (2007a) that allows for long memory dynamics, we reconfirm the characteristic of the series. Building on previous studies, this paper provides favorable support for the long-run Fisher hypothesis and help to solve an intertemporal consumption behavior puzzle across the emerging and advanced countries. Finally, the results for the G-7 countries are presented for comparison.

Diarrhées chroniques du nourrisson et de l’enfant

This paper investigates the stationarity behavior of the ex-post real interest rates (RIRs) for 12 Asian countries. Formal tests conducted indicate that high persistence is an intrinsic characteristic in the majority of the RIRs. We consider local-persistent model to assess the degree of persistence in these series. The findings from this devise reveal that RIRs are persistent, but are characterized by a mean-reverting process. The consistency of the persistence comparable amongst the series is confirmed after accounting for the volatility of the consumption growth. Applying a test proposed by Leybourne et al. (2007a) that allows for long memory dynamics, we reconfirm the characteristic of the series. Building on previous studies, this paper provides favorable support for the long-run Fisher hypothesis and help to solve an intertemporal consumption behavior puzzle across the emerging and advanced countries. Finally, the results for the G-7 countries are presented for comparison.

Testing hysteresis effect in U.S. state unemployment: new evidence using a nonlinear quantile unit root test

ABSTRACTWe revisit hysteresis effect in the unemployment rate of each of the 52 states of the United States using nonlinear quantile unit root test over the period 1976M1–2016M7. Our results indicate that unemployment rate of the U.S. economy as a whole displays hysteresis effect over recessionary periods. Nineteen out of 52 states display hysteresis behaviour over the period 1976–2016. For the remaining 33 states, we find four types of behaviours. Some states display stationarity behaviour almost in all quantiles. Some display hysteresis over recessionary periods and in contrast some display hysteresis over expansion period.

Do China mainland and SARs constitute an optimal currency area? Evidence from nonlinearity and stationarity behavior testing on real exchange rates

In this article, we use the unrestricted two-regime autoregressive threshold model to test both nonlinearity and stationarity of China’s real exchange rate against its Hong Kong and Macau special administrative regions (SARs). Our main finding is that China’s real exchange rate is neither linear nor stationary, indicating that the purchasing power parity does not hold between China Mainland and its two SARs, which implies, to certain extent, the three economies may not meet the condition of constituting an optimal currency area.

Theoretical complex Stark energies of hydrogen by a complex-scaling plus B-spline approach.

The complex-scaled (r\ensuremath{\rightarrow}${\mathit{re}}^{\mathit{i}\mathrm{\ensuremath{\theta}}}$) Stark Hamiltonian of hydrogen is diagonalized with a B-spline basis. Accurate complex energies of low-lying resonances are obtained for a wide range of electric-field strength (from 0.03 to 2.0 a.u.). The high accuracy is attributed to the good stationarity behavior of \ensuremath{\theta} trajectories with a well-adjusted B-spline basis.