Estimating Markov-Switching ARMA Models with Extended Algorithms of Hamilton

This paper proposes two innovative algorithms to estimate a general class of N-state Markov-switching autoregressive moving-average (MS-ARMA) models with a sample of size T. To resolve the problem of NT possible routes induced by the presence of MA parameters, the first algorithm is built on Hamilton’s (1989) method and Gray’s (1996) idea of replacing the lagged error terms with their corresponding conditional expectations. We thus name it as the Hamilton-Gray (HG) algorithm. The second method refines the HG algorithm by recursively updating the conditional expectations of these errors and is named as the extended Hamilton-Gray (EHG) algorithm. The computational cost of both algorithms is very mild, because the implementation of these algorithms is very much similar to that of Hamilton (1989). The simulations show that the finite sample performance of the EHG algorithm is very satisfactory and is much better than that of the HG counterpart. We also apply the EHG algorithm to the issues of dating U.S. business cycles with the same real GNP data employed in Hamilton (1989). The turning points identified with the EHG algorithm resemble closely to those of the NBER’s Business Cycle Dating Committee and confirm the robustness of the findings in Hamilton (1989) about the effectiveness of Markov-switching models in dating U.S. business cycles.Markov-switching, ARMA process

Benefit Evaluation of the Country of Origin Labeling in Taiwan: Results from Auction Experiment

This research is aimed at investigating the consumer’s preference for food produced in Taiwan and the economic benefits for the country of origin labeling. The study uses both experimental auction and contingent valuation method (CVM) to investigate factors that affect the consumer’s willingness to pay (WTP) for products under country-of-origin labeling (COOL). Experimental auctions of Taiwan and China preserved olives as well as Taiwan, China and Vietnam oolong teas were conducted using the Vickrey’s second price sealed bid auction. For CVM, the study used the double-bounded dichotomous choice method in which we started assuming the same base price for all products in the first question and then varied the prices in the second CV question. The products not chosen in the first question were offered with a discount in a range from 10% to 50% in the following question. Based on auction data, the Tobit model shows that the estimated premiums are 58.1%, 78.15% and 98.13% for Taiwan products over their alternatives of China olives, China oolong tea, and Vietnam oolong tea, respectively. Based on the CVM, the estimated premiums for Taiwan over China olives from a Logit model is 67%, and the premiums for Taiwan produced oolong tea should lie between 50% to an unknown upper bound over China and Vietnam alternatives as the Multinomial Logit model cannot be successfully estimated due to too few choice switches with discounted prices. The study thus demonstrates the superiority of the experimental auction over the CVM in eliciting the WTP for foods produced in Taiwan. The study concludes that enacting a COOL law would increase economic benefits to consumers in Taiwan, and at the same time, placing the imported products in the level playing field.country-of-origin labeling, experimental auction, Tobit model, contingent valuation method, logit model, multinomial logit model, willingness to pay, Agricultural and Food Policy, Consumer/Household Economics, Demand and Price Analysis, Food Consumption/Nutrition/Food Safety, Q13, D12.,