The Significant Effects of the COVID-19 on Leisure and Hospitality Sectors: Evidence From the Small Businesses in the United States

This paper uses the daily seasonally-adjusted data for net revenues and openings of small businesses in the accommodation, food services, leisure, and hospitality sectors in the United States from January 10, 2020, to June 24, 2021. The results from the Dorta-Sanchez bootstrap unit-root test for a random walk with drift show that the COVID-19 crisis has significantly affected revenues and openings of small leisure and hospitality firms. Moreover, the results remain valid when the data for the national level and 51 states are considered.

Bootstrap unit-root test for random walk with drift: The bsrwalkdrift command

In this article, we introduce the command bsrwalkdrift, which is primarily intended to perform a bootstrap unit-root test under the null hypothesis of random walk with drift. The method implemented in this command is considerably more precise than the corresponding case of the conventional augmented Dickey–Fuller test, which can be inaccurate when the true value of the drift term is small relative to the standard deviation of the innovations. The command also has an option to account for deterministic linear trend and another option to perform bootstrap unit-root tests under the null hypothesis of random walk without drift.

MODEL PERILAKU NET BUYING SELING (NBS) UNTUK SAHAM HMSP SELAMA PERIODE AKUISISI DARI PHILIP MORRIS

Dalam akuisisi di perusahaan yang memiliki reputasi hebat di pasar riil dan pasar keuangan, maka analisis faktor dampak dari akuisisi tersebut bagi investor pasar modal adalah penting untuk dilakukan. Hal ini karena setelah akuisisi akan terjadi perubahan struktur bisnis dan pemilik yang akan mempengaruhi arah kebijakan peusahaan di pasar modal dan biasanya ini dinantikan oleh para investor. Seperrti kasus go private Aqua pasca diambil alih Danone dan Semen Padang dan Tonasa oleh Cemex, maka akuisisi Philip Morris ke Sampoerna akan begitu dinantikan. Dengan begitu studi ini akan fokus pada varaibel net buying selling yang menjadi ukuran langsung dalam proses akuisisi. Hal ini dikarenakan dalam akusisi akan terjadi proses pembelian (penyerahan) dan penjualan (pelepasan) saham dari pemilik ke pihak pengakusisinya. Studi ini masih bersifat awal dalam topik penelitian sejenis, karenanya akan memakai model peramalan ARIMA (teknik Box Jenkins). Berdasarkan analisis ekonometrika secara time series mulai dengan uji stasioneritas ternyata terbukti bahwa variabel net buying selling sudah stasioner tanpa differencing prosess. Kedua hasil uji stasioneritas yakni uji korelogram membuktikan dari lag 1 - 28 tanda * atau spike dari net buying selling masih dalam batas garis Barlett untuk grafik ACF dan PACF. Sedangkan berdasarkan uji unit root ADF (random walk with drift and trend) terbukti nilai ADF-statistik sebesar -6.032041 masih lebih kecil dari nilai ADF-kritis (α=5%). Kemudian waktu melakukan uji identifikasi model mulai AR(1), MA(1), ARMA (1,1) yang akhirnya didapat model terbaik yakni ARMA (1,1). Model ARMA (1,1) selanjutnya dipakai sebagai model prediksi bagi para investor. In an acquisition in a company that has a great reputation in the real market and financial market, it is important to analyze the impact factor of the acquisition on capital market investors. This is because after the acquisition there will be a change in the structure of the business and the owner which will influence the direction of the company's policy in the capital market and this is usually expected by investors. As with the case of going private Aqua after being taken over by Danone and Semen Padang and Tonasa by Cemex, the acquisition of Philip Morris to Sampoerna will be expected. That way this study will focus on net buying selling variables which are a direct measure of the acquisition process. This is because in the acquisition there will be a process of buying (handing in) and selling (releasing) shares from the owner to the acquirer. This study is still preliminary in the topic of similar research, therefore it will use the ARIMA forecasting model (Box Jenkins technique). Based on the time series analysis of econometrics starting with the stationarity test it turns out that the net buying selling variable is stationary without differencing processes. The two stationary test results, the corelogram test, prove that lag 1 - 28 sign * or spike of net buying selling is still within the limits of the Barlett line for ACF and PACF charts. While based on the ADF root unit test (random walk with drift and trend) the ADF-statistic value proved to be -6.032041 still smaller than the ADF-critical value (α = 5%). Then when testing the model identification starting from AR (1), MA (1) and ARMA (1,1) which finally the best model is obtained, namely ARMA (1,1). The ARMA model (1.1) is then used as a prediction model for investors.

Is It Possible to Beat the Random Walk Model in Exchange Rate Forecasting? More Evidence for Brazilian Case.

The seminal study of Meese et al. (1983) on exchange rate forecastability had a great impact on the international finance literature. The authors showed that exchange rate forecasts based on structural models are worse than a naive random walk. This result is known as the Meese--Rogoff (MR) puzzle. Although the validity of this result has been checked for many currencies, studies for the Brazilian currency are not common. In 1999, Brazil adopted the dirty floating exchange rate regime. Rossi (2013) ran an extensive study on the MR puzzle but did not analyse Brazilian data. Our goal is to run a “pseudo real-time experiment” to investigate whether forecasts based on econometric models that use the fundamentals suggested by the exchange rate monetary theory of the 80s can beat the random model for the case of the Brazilian currency. Our work has three main differences with respect to Rossi (2013). We use a bias correction technique and forecast combination in an attempt to improve the forecast accuracy of our projections. We also combine the random walk projections with the projections of the structural models to investigate if it is possible to further improve the accuracy of the random walk forecasts. However, our results are quite in line with Rossi (2013). We show that it is not difficult to beat the forecasts generated by the random walk with drift using Brazilian data, but that it is quite difficult to beat the random walk without drift. Our results suggest that it is advisable to use the random walk without drift, not only the random walk with drift, as a benchmark in exercises that claim the MR result is not valid.

A MODELIZACIÓN DOS CAMBIOS NA LONXEVIDADE DA POBLACIÓN DO PAÍS BASCO E A SÚA ESTIMACIÓN FUTURA

O obxectivo deste traballo é estimar a tendencia futura da mortaldade da poboación doPaís Basco a través da mellora da mortaldade para o período 1991-2013, para o cal oestudo é validable. A investigación realízase a través dun modelo estocástico bietápico aoque realizamos dúas achegas. Por unha banda, unha información inicial supervisada queposibilitará prognosticar mellor o avellentamento da poboación do País Basco baixo oscriterios de Solvencia II. E por outra, na estimación inclúese unha variante na extensión doparámetro do tempo de calendario mediante unha regresión logarítmica lineal no canto dacoñecida “random walk with drift”.