Real investment and dividend policy in a dynamic stochastic general equilibrium (DSGE) model. Corporate finance at an aggregate level through DSGE models.

In this thesis, I take a theoretical dynamic stochastic general equilibrium (DSGE) approach to investigate optimal aggregate dividend policy. I make the following contribution: 1. I extend the standard DSGE model to incorporate a residual dividend policy, external financing and default and find that simulated optimal aggregate payouts are much more volatile than the observed data when other variables are close to the values observed in the data. 2. I examine the sensitivity of optimal aggregate dividend policy to the level of the representative agent¿s habit motive. My results show that, when the habit motive gets stronger, the volatility of optimal aggregate payouts increases while the volatility of aggregate consumption decreases. This is consistent with the hypothesis that investors use cash payouts from well diversified portfolios to help smooth consumption. 3. I demonstrate that the variability of optimal aggregate payouts is sensitive to capital adjustment costs. My simulated results show that costly frictions from changing the capital base of the firm cause optimal aggregate dividends and real investments to be smooth and share prices to be volatile. This finding is consistent with prior empirical observations. 4. I run simulations that support the hypothesis that optimal aggregate dividend policy is similar when the representative firm is risk averse to when it has capital adjustment costs. In both cases, optimal aggregate dividends volatility is very low. 5. In all calibrated DSGE models, apart from case 4, optimal aggregate payouts are found to be countercyclical. This supports the hypothesis that corporations prefer to hold more free cash flows for potential investment opportunities instead of paying dividends when the economy is booming, but is inconsistent with observed data. Keywords: Dynamic Stochastic General Equilibrium (DSGE), real business cycle, utility function, habits, dividend

Constrained K-means and Genetic Algorithm-based Approaches for Optimal Placement of Wireless Structural Health Monitoring Sensors

Optimal placement of wireless structural health monitoring (SHM) sensors has to consider modal identification accuracy and power efficiency. In this study, two-tier wireless sensor network (WSN)-based SHM systems with clusters of sensors are investigated to overcome this difficulty. Each cluster contains a number of sensor nodes and a cluster head (CH). The lower tier is composed of sensors communicating with their associated CHs, and the upper tier is composed of the network of CHs. The first step is the optimal placement of sensors in the lower tier via the effective independence method by considering the modal identification accuracy. The second step is the optimal placement of CHs in the upper tier by considering power efficiency. The sensors in the lower tier are partitioned into clusters before determining the optimal locations of CHs in the upper tier. Two approaches, a constrained K-means clustering approach and a genetic algorithm (GA)-based clustering approach, are proposed in this study to cluster sensors in the lower tier by considering two constraints: (1) the maximum data transmission distance of each sensor; (2) the maximum number of sensors in each cluster. Given that each CH can only manage a limited number of sensors, these constraints should be considered in practice to avoid overload of CHs. The CHs in the upper tier are located at the centers of the clusters determined after clustering sensors in the lower tier. The two proposed approaches aim to construct a balanced size of clusters by minimizing the number of clusters (or CHs) and the total sum of the squared distance between each sensor and its associated CH under the two constraints. Accordingly, the energy consumption in each cluster is decreased and balanced, and the network lifetime is extended. A numerical example is studied to demonstrate the feasibility of using the two proposed clustering approaches for sensor clustering in WSN-based SHM systems. In this example, the performances of the two proposed clustering approaches and the K-means clustering method are also compared. The two proposed clustering approaches outperform the K-means clustering method in terms of constructing balanced size of clusters for a small number of clusters. Doi: 10.28991/CEJ-2022-08-12-01 Full Text: PD

A Statistical Meta-Analysis of the Design Components of New Urbanism on Housing Prices

The principles of New Urbanism such as increased density, mixed land uses and street connectivity are often recommended in response to the typical conditions of suburban developments. Much current empirical research has begun to test whether these principles can increase property values. The findings of these empirical studies have, however, been quite inconsistent. This research attempts to quantitatively synthesize these conflicting findings through a statistical meta-analysis. This study found that a lower density, decreased street connectivity and a closer proximity to a transit stop contributed to increased housing premiums, while mixed land uses were not shown to always do so

Aggregate dividends and consumption smoothing

We show that net equity payouts from the corporate sector play a crucial role in helping individuals manage their consumption path across the business cycle. In particular, we show that, as investors’ desire to smooth consumption increases, optimal aggregate dividends become both more volatile and more counter-cyclical to help counterbalance pro-cyclical labor income. These findings are robust to whether or not agency conflicts exist in the economy

S-Petasin, the Main Sesquiterpene of Petasites formosanus, Inhibits Phosphodiesterase Activity and Suppresses Ovalbumin-Induced Airway Hyperresponsiveness

S-Petasin is the main sesquiterpene of Petasites formosanus, a traditional folk medicine used to treat hypertension, tumors and asthma in Taiwan. The aim of the present study was to investigate its inhibitory effects on phosphodiesterase (PDE) 1–5, and on ovalbumin (OVA)-induced airway hyperresponsiveness (AHR) in a murine model of allergic asthma. S-Petasin concentration-dependently inhibited PDE3 and PDE4 activities with 50% inhibitory concentrations (IC50) of 25.5, and 17.5 μM, respectively. According to the Lineweaver-Burk analysis, S-petasin competitively inhibited PDE3 and PDE4 activities with respective dissociation constants for inhibitor binding (Ki) of 25.3 and 18.1 μM, respectively. Both IC50 and Ki values for PDE3 were significantly greater than those for PDE4. S-Petasin (10–30 μmol/kg, administered subcutaneously (s.c.)) dose-dependently and significantly attenuated the enhanced pause (Penh) value induced by methacholine (MCh) in sensitized and challenged mice. It also significantly suppressed the increases in total inflammatory cells, lymphocytes, neutrophils, eosinophils and levels of cytokines, including interleukin (IL)-2, IL-4 and IL-5, tumor necrosis factor (TNF)-α and interferon (IFN)-γ in bronchoalveolar lavage fluid (BALF) of these mice. In addition, S-petasin (10–30 μmol/kg, s.c.) dose-dependently and significantly attenuated total and OVA-specific immunoglobulin E (IgE) levels in the serum and BALF, and enhanced the IgG2a level in serum of these mice. The PDE4H value of S-petasin was >300 μM; therefore, its PDE4H/PDE4L value was calculated to be >17. In conclusion, the present results for S-petasin at least partially explain why Petasites formosanus is used as a folk medicine to treat asthma in Taiwan

Quantitative measures of functional outcomes and quality of life in patients with C5 palsy

AbstractBackgroundIt is generally understood that postoperative C5 palsy can occur with anterior or posterior decompression surgery, but functional measures of the palsy have not been well documented. This study aimed to investigate the incidence of C5 palsy in different surgical procedures, examine the correlations between muscle strength, upper extremity functional measures, and health-related quality of life, and to observe potential risk factors contributing to C5 palsy.MethodsOur investigation involved a retrospective study design. A total of 364 patients who underwent decompression surgery were indicated within the selected exclusion criteria. Additionally, 12 C5 palsy patients were recruited. The relationships between the manual muscle test (MMT), the action research arm test (ARAT), the Jebsen test of hand function (JTHF), and the European quality of life-5 dimensions (EQ-5D) were studied, and univariate analyses were performed to search possible risk factors and recovery investigation.ResultsThe data analyzed in the 12 cases and C5 palsy incidences (3.3%) were: 0.7% in anterior procedures (n = 2), 8.8% in posterior procedures (n = 6), and 36.4% in combined procedures (n = 4). Moderate-to-high correlations were observed between the ARAT, JTHF, EQ-5D visual analog scale scores, and MMT (r = 0.636–0.899). There were significant differences in patient age, etiology of cervical lesion, variable decompression procedures, and the number of decompression levels between the C5 palsy and non-C5 palsy groups. For female patients (p = 0.018) and number of decompression levels (p = 0.028), there were significant differences between the complete recovery and the incomplete recovery groups.ConclusionPatients undergoing combined anterior–posterior decompression surgery had the highest incidence of C5 palsy, and correlations between the ARAT, JTHF, EQ-5D visual analog scale clinical tools, and MMT scores supported these findings. Female status and lower decompression levels could also be predictive factors for complete recovery, although additional research is needed to substantiate these findings

Genomic Signatures of Human versus Avian Influenza A Viruses

Fifty-two species-associated amino acid residues were found between human and avian influenza viruses

Peculiar optical properties of bilayer silicene under the influence of external electric and magnetic fields

We conduct a comprehensive investigation of the effect of an applied electric field on the optical and magneto-optical absorption spectra for AB-bt (bottom-top) bilayer silicene. The generalized tightbinding model in conjunction with the Kubo formula is efficiently employed in the numerical calculations. The electronic and optical properties are greatly diversified by the buckled lattice structure, stacking configuration, intralayer and interlayer hopping interactions, spin-orbital couplings, as well as the electric and magnetic fields (Ez ˆz & Bz ˆz ). An electric field induces spin-split electronic states, a semiconductor-metal phase transitions and the Dirac cone formations in different valleys, leading to the special absorption features. The Ez-dependent low-lying Landau levels possess lower degeneracy, valley-created localization centers, peculiar distributions of quantum numbers, well-behaved and abnormal energy spectra in Bz-dependencies, and the absence of anti-crossing behavior. Consequently, the specific magneto-optical selection rules exist for diverse excitation categories under certain critical electric fields. The optical gaps are reduced as Ez is increased, but enhanced by Bz, in which the threshold channel might dramatically change in the former case. These characteristics are in sharp contrast with those for layered graphene

MiniZero: Comparative Analysis of AlphaZero and MuZero on Go, Othello, and Atari Games

This paper presents MiniZero, a zero-knowledge learning framework that supports four state-of-the-art algorithms, including AlphaZero, MuZero, Gumbel AlphaZero, and Gumbel MuZero. While these algorithms have demonstrated super-human performance in many games, it remains unclear which among them is most suitable or efficient for specific tasks. Through MiniZero, we systematically evaluate the performance of each algorithm in two board games, 9x9 Go and 8x8 Othello, as well as 57 Atari games. For two board games, using more simulations generally results in higher performance. However, the choice of AlphaZero and MuZero may differ based on game properties. For Atari games, both MuZero and Gumbel MuZero are worth considering. Since each game has unique characteristics, different algorithms and simulations yield varying results. In addition, we introduce an approach, called progressive simulation, which progressively increases the simulation budget during training to allocate computation more efficiently. Our empirical results demonstrate that progressive simulation achieves significantly superior performance in two board games. By making our framework and trained models publicly available, this paper contributes a benchmark for future research on zero-knowledge learning algorithms, assisting researchers in algorithm selection and comparison against these zero-knowledge learning baselines. Our code and data are available at https://rlg.iis.sinica.edu.tw/papers/minizero.Comment: Submitted to IEEE Transactions on Games, under revie