This paper studies the residual empirical process of longand short-memory time series regression models and establishes its uniform expansion under a general framework. The results are applied to the stochastic regression models and unstable autoregressive models. For the long-memory noise, it is shown that the limit distribution of the Kolmogorov–Smirnov test statistic studied in Ho and Hsing ...

Internet and mobile banking deliver services through various cashless payment tools, such as debit credit cards, direct transfers electronic wallets. The usage of internet in Malaysia has increased, but it is uncertain if they facilitate retail consumption. If are the preferred services, their could stimulate consumption; otherwise, will be short-lived more work must done to develop sector. Thi...

The study investigated the impact of monetary policy on unemployment rate in Nigeria. Time series data spanning from 1981 to 2020 was sourced Central Bank Nigeria statistical bulletin and national bureau statistics (various editions). ARDL bounds testing approach co-integration used analyse data. Autoregressive Distributed Lag (ARDL) model Error Correction Model (ECM) were utilized address main...

The limiting distribution of the quantile estimate for the autoregressive coefficient of a near-integrated first order autoregressive model with infinite variance errors is derived. Since the limiting distribution depends on the unknown density function of the errors, an empirical likelihood ratio statistic is proposed from which confidence intervals can be constructed for the near unit root mo...

The human capital school of thought considers education in primary and secondary as the foundation for development that promotes economic growth. Persuaded by an empiricist paradigm this study used Autoregressive Distributed Lag (ARDL) bounds testing analysis was conducted to examine short long run relationship between growth South Africa. Economic growth, data from 2002 2018 used. diagnostic t...

This paper analyzes the delays and therefore the unpredictability of foreign aid in Africa. As many African countries are dependant to foreign aid, it’s important to understand to what extent aid delays matters for the absorptive capacity and therefore influences aid effectiveness. As the aid literature on absorptive capacity was mainly focused on dutch disease, decreasing returns and instituti...

We studied the extent to which bitcoin blockchain security permanently depends on underlying distribution of cryptocurrency market outcomes using daily and data for 2014–2019 employing autoregressive-distributed lag (ARDL) approach. tested three equilibrium hypotheses: (i) sensitivity mining reward, (ii) proof-of-work cost, (iii) speed adjustment deviations from path. Our results suggest that p...

SUMMARY This paper investigates the finite sample distribution of the least squares estimator of the autoregressive parameter in a first-order autoregressive model. Uniform asymptotic expansion for the distribution applicable to both stationary and nonstationary cases is obtained. Accuracy of the approximation to the distribution by a first few terms of this expansion is then investigated. It i...

Trade duration and daily range data often exhibit asymmetric shape with long right tail. In analysing the dynamics of these positively valued time series under autoregressive conditional duration (ACD) models, the choice of the conditional distribution for innovations has posed challenges. A suitably chosen distribution, which is capable of capturing unique characteristics inherent in these dat...

Forecasting time series data is an important subject in economics, business, and finance. Traditionally, there are several techniques to effectively forecast the next lag of time series data such as univariate Autoregressive (AR), univariate Moving Average (MA), Simple Exponential Smoothing (SES), and more notably Autoregressive Integrated Moving Average (ARIMA) with its many variations. In par...