The determinants of Latin American exchange rate regimes

The experience of the last thirty years suggests that a wide range of factors affects policymakers’ choice of exchange rate regime. The initial explanation was that changes in the international sphere dominated domestic policies and strongly influenced how governments decided among the trade-offs. More recently, domestic political factors’ influence on the choice of exchange rate regimes have been emphasized, providing detailed and rich insights into the dynamics of the choice. Neither approach has been entirely successful. Both internal and external factors must be taken into account. This article builds on previous empirical work and takes into account domestic and international influences on the choice of exchange rate regimes in Latin America between 1964 and 1996. In addition, we highlight a variety of ‘interactions’, choices of economic policy that are affected by both national and international pressures and that, in turn, influence the choice of exchange rate regime. The empirical model uses multinomial ordered logit analysis to determine the factors in exchange rate determination and to compare the explanatory of the models with and without the interaction variables.     

Testing long-run neutrality using intra-year data

Previous tests of the long-run neutrality hypothesis have generally relied on annual time series data. This paper analyses the long-run neutrality of money in Australia using different sources of intra-year data, which permits an examination of the effects of seasonality and the robustness of previous empirical results. A reduced form ARIMA model is used with both quarterly seasonally unadjusted and adjusted Australian real GDP and nominal money supply to test the neutrality hypothesis. Using two measures of money stock, namely M1 and M3, it is shown that the hypothesis is supported using M1 as the measure of money supply, while it is rejected using M3. Recent trends and developments in the money and credit markets in Australia provide a possible explanation of the sensitivity of the outcome to the measure of money stock employed in the analysis.     

Hedonic price indexes and the distribution of buyers across the product space: an application to mainframe computers

In this article we present the Silverman multimodality test and mixture distributions methodology, applying both approaches to the Survey of Economic Expectations of the Central Bank of Chile. The main results reflect the importance of a permanent monitoring of the complete distributions and not just central tendency meausures as is the practice in many central banks currently. We find that the forecasts of the private professional forecasters have systematically been in line with the inflation targeting range, although during episodes where the effective inflation proved to be outside the target range.     

Economic analysis of BRAF gene mutation testing in real world practice using claims data: costs of single gene versus panel tests in patients with lung cancer

Aims: To assess the time to BRAF testing, compare the characteristics of tested vs not-tested patients, and describe the costs for sequential vs next-generation sequencing (NGS) BRAF testing.

Methods: Patients diagnosed with lung cancer after December 1, 2013 were identified from two US claims databases; their characteristics were assessed during the 12 months before diagnosis (index date). Testing modalities were analyzed from the index date to end of continuous health plan enrollment or data availability (December 2015), based on combinations of Current Procedural Terminology (CPT) procedure codes. Time to BRAF testing was assessed using Kaplan-Meier analysis. Costs were analyzed from a payer’s perspective.

Results: A total of 28,011 patients newly-diagnosed with lung cancer were identified. Of them, 1,260 (4.5%) were tested for BRAF: 3.2% and 4.2% were tested at 6 and 12 months, respectively, after the index date. Compared to non-tested patients, tested patients were younger (58.3 vs 65.3 years; p?<?.001), had a lower Charlson Comorbidity Index (2.8 vs 2.9; p?=?.005), and a higher proportion had metastases (70.9% vs 43.4%; p?<?.001). In 76.0% of cases, BRAF was tested along with KRAS. BRAF was tested using NGS in 6.6% of cases. The average reimbursed amounts for the 10 most common CPT code combinations were $207–$2,074. Using the average costs of individual mutation tests, the total cost of sequential testing comprising KRAS, EGFR, ALK, ROS1, and BRAF tests was $3,763 ($464, $696, $1,070, $1,127, and $406, respectively), that of NGS was $2,860.

Limitations: Claims data did not include BRAF test results.

Conclusions: Among patients newly-diagnosed with lung cancer, 4.5% were tested for BRAF. Tested patients were younger and had a lower comorbidity burden, but more advanced disease. While reimbursed amounts varied greatly based on combinations of testing procedures, NGS testing was associated with cost savings compared to sequential testing of individual mutations.     

Global competitive conditions driving the manufacturing location decision

Given today's rapidly shifting global competitive conditions—including customer location, natural disasters, currency valuation, labor and transportation costs and availability—many U.S. companies are revisiting decisions about their preferred manufacturing location(s). The purpose of this research is to understand some of the trends that affect whether U.S.-based companies bring their production back to the United States or relocate it to different geographical locations (reshore). The focus is on the key factors that affect companies’ manufacturing location decisions, the importance of these factors, and how the importance has changed over time. Because of the complexity involved in the manufacturing location decision, key risk factors inherent in the manufacturing decision are also assessed. Survey responses from 319 companies that currently manage offshore manufacturing plants are analyzed. Among other insights, this study found that 40% of these companies perceived a trend toward reshoring to the U.S. in their industries. The companies involved in this study also place an increasing importance on where their customers want them to locate, as well as how the location could help expand into new customer markets. These and further results and implications for U.S. manufacturing companies are presented herein.