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- Byusa, Vincent
(author)
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Money demand, real effective exchange rates, and uncertainty
- 2024
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Doctoral thesis (other academic/artistic)abstract
- This PhD thesis consists of three distinct but interrelated research papers that collectively explore critical aspects of money demand, real effective exchange rates behavior, and uncertainty in different contexts. The first paper examines the nature of money demand in Rwanda and the rationale for the country’s monetary policy shift to inflation targeting in 2019, providing evidence of long-run money demand stability despite uncertainties affecting the global economy, and challenging the view that monetary aggregates should have no role in Rwanda’s monetary policy. The second paper investigates the complex effects of grant revenues on real effective exchange rates in Sub-Saharan African countries, revealing the outcomes of short-run depreciation and long-run appreciation. The last paper assesses how exchange rate regime choice affects the degree and persistence of real effective exchange rate misalignments, showing that, relative to a floating exchange rate regime, fixed and intermediate regimes effectively limit misalignment size, although with higher persistence. Together, these papers offer nuanced insights into the interaction between the money market, uncertainty, external grants, and exchange rate regime, underscoring the need for careful policy consideration to ensure economic stability and competitive currency values.
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| 2. |
- Omer, Talha
(author)
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Shrinkage estimation methods for mixed data sampling regression and heterogeneous autoregressive models
- 2024
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Doctoral thesis (other academic/artistic)abstract
- This thesis consists of four research articles. The first two articles assess the effectiveness of various shrinkage estimation methods within mixed data sampling (MIDAS) regression models and find that our proposed methods have superior performance compared to existing models. The third article extends MIDAS models to encompass count data, and the fourth article evaluates the performance of a specific proposed shrinkage method in forecasting stock price volatility.In the first article, which focuses on MIDAS regression in a nonparametric way, two-parameter nonparametric shrinkage estimation methods are developed to estimate the MIDAS regression parameters. The proposed methodology is compared with one-parameter nonparametric and parametric MIDAS regression, both theoretically via simulation and practically in terms of forecasting U.S. inflation rates. The proposed two-parameter estimator outperforms the one-parameter estimator and other comparative methods, both theoretically and empirically.In the second article, the two-dimensional panel data regression model is extended to a multidimensional context for mixed-frequency data. We use the least absolute shrinkage and selection operator (LASSO), sparse group (sg)-LASSO, and elastic net unrestricted MIDAS (U-MIDAS) for estimation. The theoretical properties of the extended models are evaluated using Monte Carlo simulations. The proposed model is empirically applied to now cast three-dimensional home ownership vacancy rates across states, metropolitan statistical areas (MSAs), and time in the U.S. Finally, we compare the predictive performance of this extended model with the traditional three-dimensional panel data regression model. The extended model demonstrates superior performance over traditional multidimensional methods, both theoretically and empirically.The third article introduces a generalized Poisson regression model for count time series data, applied within a MIDAS framework. The new MIDAS Poisson regression model (MIDAS-PRM) is used to forecast the monthly dengue counts from high-frequency environmental parameters and Google Trends data.Forecasts are generated using a rolling window forecast scheme and forecast combinations. We conclude that the proposed MIDAS-PRM significantly enhances predictive performance compared to the standard time series PRM and other benchmark time series models.The fourth article proposes two-parameter ridge shrinkage estimation methods to estimate the realized volatility (RV) of the heterogeneous autoregressive (HAR) model. The proposed estimator, which is notable for its orthogonality properties, is employed to forecast the RV of stock prices. The proposed estimator is evaluated through simulations and empirical applications, demonstrating superior performance both theoretically and empirically compared to traditional methods.
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| 3. |
- Shen, Qing, et al.
(author)
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Risk of Injuries around Diagnosis of Cervical Cancer and Its Precursor Lesions : A Nationwide Cohort Study in Sweden
- 2020
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In: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 29:11, s. 2230-2234
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Journal article (peer-reviewed)abstract
- BACKGROUND: Highly increased risk of injuries has been noted around the time of cancer diagnosis. Whether there is a similar increase in risk around the diagnosis of cervical cancer and its precursor lesions was unknown.METHODS: We performed a cohort study including 3,016,307 Swedish women that participated in cervical screening during 2001 to 2012. We calculated the incidence rates (IR) of hospitalized iatrogenic or noniatrogenic injuries during the diagnostic workup, and the time interval from smear or punch biopsy until surgical treatment or 2 months after the last smear or biopsy, among women with invasive cervical cancer (ICC) or its precursor lesions. We calculated the IRs of injuries during the 2 months after a normal smear among the other women as reference. IR ratios (IRR) and 95% confidence intervals (CI) were calculated using Poisson regression.RESULTS: (IR, 0.09 per 1,000 person-months; IRR, 3.04; 95% CI, 1.73-5.34). We also found an increased rate of noniatrogenic injuries during the diagnostic workup of women with invasive cancer (IR, 0.65 per 1,000 person-months; IRR, 2.48; 95% CI, 1.30-4.47).CONCLUSIONS: Although rare, there was an increased risk of inpatient care for iatrogenic and noniatrogenic injuries during the diagnostic workup of women with ICC.IMPACT: Women experienced burden of medical complications and psychologic distress around diagnosis of a potential cervical cancer.
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