Assessing macroeconomic forecasts for Japan under an asymmetric loss function

Tsuchiya, Yoichi

doi:10.1016/j.ijforecast.2015.05.005

Cited by 14 publications

(5 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Krüger and LeCrone (2019) show that this method has a high power and is robust to fat tails, serial correlation, and outliers. The method has been used to evaluate forecasts of a number of economic variables by professional forecasters (Aretz, Bartram, and Pope 2011;Pierdzioch, Rülke, and Stadtmann 2013; Mamatzakis and Koutsomanoli‐Filippaki 2014; Fritsche et al 2015; Pierdzioch, Reid, and Gupta 2016; Tsuchiya 2016a, 2016b; Christodoulakis 2020), government agencies (Auffhammer 2007; Krol 2013; Tsuchiya 2016a; Giovannelli and Pericoli 2020), international organizations (Christodoulakis and Mamatzakis 2008; Tsuchiya 2016a; Giovannelli and Pericoli 2020), and central banks (Capistrán 2008; Baghestani 2013; Pierdzioch, Rülke, and Stadtmann 2015; Ahn and Tsuchiya 2019; Caunedo et al 2020). These studies overwhelmingly suggest that forecasts that are biased or inefficient under MSE loss are rational under asymmetric loss.…”

Section: Introductionmentioning

confidence: 99%

The Rationality of USDA Forecasts under Multivariate Asymmetric Loss

Bora¹,

Katchova²,

Kuethe³

2020

American J Agri Economics

View full text Add to dashboard Cite

A large number of previous studies suggest that many USDA forecasts are biased and/or inefficient. These findings, however, may be the result of the assumed loss function of USDA forecasters. We test the rationality of the USDA net cash income forecasts and the WASDE production and price forecasts between 1988 and 2018 using a flexible multivariate loss function that allows for asymmetric loss and non‐separable forecast errors. Our results provide robust evidence that USDA forecasters are rational expected loss minimizers yet demonstrate a tendency to place a greater weight on under‐ or overprediction. As a result, this study provides an alternate interpretation of previous findings of forecast irrationality.

show abstract

Section: Introductionmentioning

confidence: 99%

The Rationality of USDA Forecasts under Multivariate Asymmetric Loss

Bora¹,

Katchova²,

Kuethe³

2020

American J Agri Economics

View full text Add to dashboard Cite

show abstract

“…Following this line of research, there has been a number of works that have aimed at fiscal forecasting (Tsuchiya, 2016). 4.…”

Section: Notesmentioning

confidence: 99%

A Dependent Economy Model of Employment, Real Exchange Rate and Debt Dynamics: Towards an Understanding of Pandemic Crisis

Basu

Nag

2021

Foreign Trade Review

View full text Add to dashboard Cite

Given the unforeseen and uncertain circumstances during the pandemic, the role of government expenditure becomes extremely relevant in sustaining lives and livelihoods of the masses. This brings forth public sector deficit as a key issue of macroeconomic policy debate. This article aims at investigating the effects of an unanticipated adverse shock like COVID-19, on the real value of public debt, in a small open economy, consisting of traded and non-traded sectors, along with proposed management of such crisis with fiscal and monetary expansion. The results of policy-induced and exogenous shocks depend on the difference in the speeds of adjustments in real exchange rate, interest rate and real value of debt, and the associated multitudes of cross effects. While an unanticipated adverse shock like COVID-19 causes contraction of both traded and non-traded sectors and reduces consumption expenditure, investment expenditure and level of employment and real value of aggregate income in the short run, fiscal expansion causes higher real value of debt and lower real exchange rate. JEL Codes: E12, E62, H63

show abstract

“…In model selection, most previous researches just selected the model that provided the most accurate predictions regardless of whether certain modeling assumptions were violated or unrealistic. Forecasting with asymmetric loss has been researched in statistic field [27] and was widely used in economic issues [28][29][30]. Zhang et al [31] used GJR-GARCH model with a conditional variance formulation to capture asymmetric response in the conditional variance in short-term traffic forecasting.…”

Section: Literature Reviewmentioning

confidence: 99%

Short-Term Traffic Volume Forecasting with Asymmetric Loss Based on Enhanced KNN Method

Wang

2019

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Short-term traffic volume forecasting is one of the most essential elements in Intelligent Transportation System (ITS) by providing prediction of traffic condition for traffic management and control applications. Among previous substantial forecasting approaches, K nearest neighbor (KNN) is a nonparametric and data-driven method popular for conciseness, interpretability, and real-time performance. However, in previous related researches, the limitations of Euclidean distance and forecasting with asymmetric loss have rarely been focused on. This research aims to fill up these gaps. This paper reconstructs Euclidean distance to overcome its limitation and proposes a KNN forecasting algorithm with asymmetric loss. Correspondingly, an asymmetric loss index, Imbalanced Mean Squared Error (IMSE), has also been proposed to test the effectiveness of newly designed algorithm. Moreover, the effect of Loess technique and suitable parameter value of dynamic KNN method have also been tested. In contrast to the traditional KNN algorithm, the proposed algorithm reduces the IMSE index by more than 10%, which shows its effectiveness when the cost of forecasting residual direction is notably different. This research expands the applicability of KNN method in short-term traffic volume forecasting and provides an available approach to forecast with asymmetric loss.

show abstract

Assessing macroeconomic forecasts for Japan under an asymmetric loss function

Cited by 14 publications

References 38 publications

The Rationality of USDA Forecasts under Multivariate Asymmetric Loss

The Rationality of USDA Forecasts under Multivariate Asymmetric Loss

A Dependent Economy Model of Employment, Real Exchange Rate and Debt Dynamics: Towards an Understanding of Pandemic Crisis

Short-Term Traffic Volume Forecasting with Asymmetric Loss Based on Enhanced KNN Method

Contact Info

Product

Resources

About