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We study business cycle fluctuations in heterogeneous agent general equilibrium models featuring intensive and extensive margins of labor supply. A nonlinear mapping from time devoted to work to labor services generates operative extensive and intensive margins. Our model captures the salient features of the empirical distribution of hours worked, including how individuals transit within this distribution. We study how various specifications influence labor supply responses to aggregate technology shocks and find that abstracting from intensive margin adjustment can have large effects on the volatility of aggregate hours even if fluctuations along the intensive margin are small.

Lightweight-foamed soils are mixed soils with foam and cement to enhance the solidity and lightness of soils. Marine wastes, especially waste fishing nets, can be additives to reinforce the engineering properties of lightweight-foamed soils. In this paper, lightweight-foamed soils reinforced with waste fishing nets were investigated. Dredged soil and waste fishing nets were collected and pre-processed for testing. For optimization, the water content, foam ratio, cement ratio, net ratio, net conditions, and curing days were evaluated with respect to workability, unit weight, and strength. The variables were narrowed down based on the performance criteria. The results found that a water content of around 100%, cement ratio of 20%, foam ratio of 5%, and net ratio of 4% with shredded nets provide the best engineering performance of lightweight-foamed soils. The use of nets presented a superior increase in critical strength rather than an obvious increase in peak strength. A normalized factor was used to predict the required strength of lightweight-foamed soils. Finally, this study proposes field implementation methods in terms of the initial conditions of soils and optimal conditions of soils, resulting in the depletion of waste fishing nets.

We demonstrate that aggregate employment and consumption can increase without a corresponding movement in productivity in a model with heterogeneous agents where the only aggregate disturbance is a productivity shock. The interaction between incomplete capital markets and indivisible labor results in a low employment-productivity correlation and creates a time-varying wedge between the marginal rate of substitution (for commodity consumption and hours) and productivity. Our results caution against viewing the measured wedge as an inefficiency due to a failure of labor-market clearing or as a fundamental driving force behind business cycles. (JEL D31, E32, J22, J24, J31)

At the aggregate level, the labor-supply elasticity depends on the reservation-wage distribution. We present a model economy where workforce heterogeneity stems from idiosyncratic productivity shocks. The model economy exhibits the cross-sectional earnings and wealth distributions that are comparable to those in the micro data. We find that the aggregate labor-supply elasticity of such an economy is around 1, greater than a typical micro estimate.

Takahashi (2014) has uncovered coding errors in our paper, Chang and Kim (2007)—henceforth, CK. We acknowledge and are embarrassed by these mistakes. We are grateful to Takahashi for uncovering them. While the correction decreases the volatility of the labor market wedge, we find that the main message of CK remains valid: the measured labor market wedge arises endogenously in an economy with incomplete capital markets and indivisible labor supply. For example, our model accounts for 18 percent of the volatility in the labor market wedge in the data; it was 43 percent in CK.

Data from a heterogeneous-agents economy with incomplete asset markets and indivisible labor supply are simulated under various fiscal policy regimes and an approximating representative-agent model is estimated. Preference and technology parameter estimates of the representative-agent model are not invariant to policy changes and the bias in the representative-agent model's policy predictions is large compared to predictive intervals that reflect parameter uncertainty. Since it is not always feasible to account for heterogeneity explicitly, it is important to recognize the possibility that the parameters of a highly aggregated model may not be invariant with respect to policy changes.

The purpose of this paper is to remove the exponentially decaying DC offset in fault current waveforms using a deep neural network (DNN), even under harmonics and noise distortion. The DNN is implemented using the TensorFlow library based on Python. Autoencoders are utilized to determine the number of neurons in each hidden layer. Then, the number of hidden layers is experimentally decided by comparing the performance of DNNs with different numbers of hidden layers. Once the optimal DNN size has been determined, intensive training is performed using both the supervised and unsupervised training methodologies. Through various case studies, it was verified that the DNN is immune to harmonics, noise distortion, and variation of the time constant of the DC offset. In addition, it was found that the DNN can be applied to power systems with different voltage levels.

We consider a matching model of employment with flexible wages for new hires but sticky wages within matches. Unlike most models of sticky wages, we allow effort to respond if wages are too high or too low. In the Mortensen-Pissarides model, employment is not affected by wage stickiness in existing matches. But it is in our model. If wages of matched workers are stuck too high, firms require more effort, lowering the value of additional labor and reducing hiring. We find that effort’s response can greatly increase wage inertia.

A large-scale ultrasonic washing instrument was developed, and its performance was evaluated using an ultrasonic instrument and mechanical washing for desalination in sea sand. Preliminary experiments with a portable ultrasonic device confirmed that increasing the ultrasonic power intensity and application time increased effectiveness of salt washing in sea sand. On the basis of these findings, a large-scale washing instrument with a maximum output of 1500 W, an ultrasonic frequency of 28 kHz, and a 25 L capacity washing tank was developed. Parametric experiments via the developed system were performed to investigate the effects of the sea-sand-to-washing water ratio, ultrasonic intensity, and washing time on washing effectiveness. The greatest reduction in salinity was observed when both ultrasonic treatment and mixing of sea sand with water were applied. The optimal washing conditions were an ultrasonic intensity of 1200 W, a washing water-to-sea sand ratio of 2:1, and a minimum washing time of 3 min. The results confirm that the developed equipment is effective for removing salt from sea sand and that further optimization of the ultrasonic intensity and mixing techniques can increase the washing efficiency.

With growing global demand for sustainable decarbonization, hydrogen energy systems have emerged as a key pillar in achieving carbon neutrality. This study assesses the greenhouse gas (GHG) reduction efficiency of Republic of Korea’s hydrogen ecosystem from a life-cycle perspective, focusing on production and utilization stages. Using empirical data—including the national hydrogen supply structure, fuel cell electric vehicle (FCEV) deployment, and hydrogen power generation records, the analysis compares hydrogen-based systems with conventional fossil fuel systems. Results show that current hydrogen production methods, mainly by-product and reforming-based hydrogen, emit an average of 6.31 kg CO2-eq per kg H2, providing modest GHG benefits over low-carbon fossil fuels but enabling up to a 77% reduction when replacing high-emission sources like anthracite. In the utilization phase, grey hydrogen-fueled stationary fuel cells emit more GHGs than the national grid. By contrast, FCEVs demonstrate a 58.2% GHG reduction compared to internal combustion vehicles, with regional variability. Importantly, this study omits the distribution phase (storage and transport) due to data heterogeneity and a lack of reliable datasets, which limits the comprehensiveness of the LCA. Future research should incorporate sensitivity or scenario-based analyses such as comparisons between pipeline transport and liquefied hydrogen transport to better capture distribution-phase impacts. The study concludes that the environmental benefit of hydrogen systems is highly dependent on production pathways, end-use sectors, and regional conditions. Strategic deployment of green hydrogen, regional optimization, and the explicit integration of distribution and storage in future assessments are essential to enhancing hydrogen’s contribution to national carbon neutrality goals.