Forecasting growth cycle turning points using US and Japanese professional forecasters

This paper examines the forecasting of growth cycle turning points by comparing the performances of US and Japanese professional forecasters with those of a simple time-series model, using real-time data. The empirical results, obtained after performing contingency table analyses and visual inspections, indicate that the US professional forecasters considerably outperform the simple time-series model; however, the Japanese professional forecaster is comparable to the simple time-series model in the visual inspections of major turning points.      

Market-specific and currency-specific risk during the global financial crisis: Evidence from the interbank markets in Tokyo and London

This paper investigates how international money markets reflected credit and liquidity risk during the global financial crisis. After matching the currency denomination, we examine how the Tokyo Interbank Offered Rate (TIBOR) was synchronized with the London Interbank Offered Rate (LIBOR). We find remarkably asymmetric responses in market-specific and currency-specific risk during the crisis. The regression results suggest that market-specific credit risk increased the difference across markets, whereas liquidity risk caused the difference across currency denominations. They also support the view that liquidity shortage of the US dollar occurred in international money markets during the crisis. Coordinated central bank liquidity provisions were useful in reducing the liquidity shortage of the US dollar, but their effectiveness was asymmetric across markets.     

Cost minimization analysis of beta-blocker at the time of CT imaging for suspected of coronary heart disease in Japan

Objectives:

To conduct a cost-minimization analysis of landiolol for CT diagnosis of coronary heart diseases in patients with tachycardia in Japan.

Methods:

A decision-tree model was constructed to analyze costs from the healthcare payer’s perspective. Drug costs and diagnosis costs, computer tomography coronary angiography (CTCA), and coronary angiography (CAG), are adopted to the model. Landiolol is administered only to slow the heart rate to take CT images appropriately. Since some trials proved that there was no difference between landiolol and placebo in terms of efficacy and safety, this study conducted cost-minimization analysis. Of those suspected of coronary heart diseases, 22.5% are thought to be taking beta-blockers. The success rates for CT scanning for landiolol and placebo, derived from domestic trial data, were 81.4% (96/118, 77.8–84.9%) and 54.2% (64/118, 49.7–58.8%). Patients who failed to take a CT image were thought to take CAG. The healthcare cost was derived from a Japanese fee schedule. Costs of landiolol, CT imaging, and CAG are JPY2634 (USD1?=?JPY100, as of November 20, 2013), JPY38,116, and JPY101,322, respectively. The positive rate for CAG, derived from domestic trial data, was 37.1% (33/89, 32.0–42.2%). Various sensitivity analyses, both univariate and probabilistic ones, were conducted.

Results:

In the base case analysis, expected costs per patient for landiolol and placebo were JPY78,956 and JPY82,232, respectively. In budget impact analysis, 81,062 patients are eligible for landiolol and it can save JPY266million for whole patients. Sensitivity analyses suggested the robustness of the results.

Limitations:

This study did not consider any adverse effects in the decision-tree model. This model was developed especially for measuring the cost-saving effect of landiolol, through decreasing the number of patients who require CAG, due to imaging failure.

Conclusions:

Landiolol for CTCA diagnosis in patients suspected of coronary heart disease with tachycardia is thought to be cost saving.     

A model selection approach for multiple indicators multiple causes model

This study proposes a model selection approach for determining the inclusion or exclusion of a latent variable when two exogenous and two endogenous variables are provided. The models compared are the multivariate regression model without latent variables (MR model) and the multiple indicators multiple causes model (MIMIC model). The inclusion of a latent variable in the MR model yields the MIMIC model. In the proposed approach, an information criterion is used to select the best model of the two. The efficacy of the proposed approach is examined through two types of simulation studies and empirical analyses of the shadow economy and the fiscal illusion.     

Regional Liquidity Risk and Covered Interest Parity During the Global Financial Crisis: Evidence from Tokyo,London, and New York*

ABSTRACT

During the global financial crisis, there were substantial deviations from covered interest parity (CIP) condition. In particular, in the post-Lehman period, the US dollar interest rate became very low on the forward market. However, the deviations from the CIP condition varied across markets. After presenting a simple model, the following analysis examines how the CIP condition between the Japanese yen and the US dollar was violated in Tokyo, London, and New York markets. We show that the CIP deviations became largest in the New York market soon after the Lehman shock but were largest in the Tokyo market in the rest of the turmoil period. The regressions suggest that market-specific credit risks and central banks’ liquidity provisions explained the difference across the markets. In particular, they indicate that larger dollar-specific risk and smaller yen-specific risk caused larger deviations in the Tokyo market.     

Evaluation of a dairy agri-environmental programme for restoring woody green infrastructure

Pastoral landscape woody vegetation provides ecosystem services, but potentially competes for space, light and nutrients that could provide additional farm production. A questionnaire determined the values and behaviours of New Zealand dairy farmers to evaluate voluntary agri-environmental programmes for restoring woody vegetation. Findings indicate the area is increasing, while the composition and configuration of networks are changing and redistributing. Farms with little are losing more, and those with more are gaining. Farmers are planting new areas to increase their public ecosystem services, but may not provide these services through planting and management. Barriers include insufficient private woody vegetation ecosystem services, and low rates of growth of native plants. Government incentive programmes are ineffective in overcoming barriers. Farmers may be motivated by stronger evidence of valued ecosystem services, information about their benefits and drawbacks and how to support services through planting and management. However, a targeted environmental stewardship scheme is required to overcome barriers to planting, with government and the dairy industry working together to develop and maintain a landscape-scaled woody vegetation network on private and public land. Such networks would build sustainability and resilience into dairy farming, leading to an equitably sharing of benefits and costs of their public ecosystem services.     

On the predictability of daytime and night-time yen/dollar exchange rates

This article first shows that the yen/dollar rate tended to appreciate in Japan daytime but to depreciate in Japan night-time in the 2000s. The result is very paradoxical because the asymmetry implies that the intra-daily yen/dollar rate had predictable stochastic trends in the 2000s. The article then investigates whether lagged dependent variables and various external shocks were responsible to the asymmetric feature. We find that once we control the effects of lagged dependent variables and external shocks, the daytime yen/dollar rate tended to appreciate when it had appreciated on the day before, while the night-time yen/dollar rate tended to depreciate when it had depreciated on the day before.     

Measuring major and minor cycles in univariate economic time series

The coexistence of cycles with different periods complicates the assessment of the current macroeconomic conditions. In order to overcome this problem, a modeling of multiple autoregressive processes in a univariate time series is presented. In the proposed model, individual autoregressive processes are assumed to be mutually uncorrelated, and the number of individual autoregressive processes is determined using information criteria. Simulation results show that the proposed procedure is sufficiently applicable for measuring major and minor cycles. Empirical applications suggest the usefulness and limitations of the proposed method.