The Short-Term Impact of Ontario's Generic Pricing Reforms

Background: Canadians pay amongst the highest generic drug prices in the world. In July 2010, the province of Ontario enacted a policy that halved reimbursement for generic drugs from the public drug plan, and substantially lowered prices for private purchases. We quantified the impact of this policy on overall generic drug expenditures in the province, and projected the impact in other provinces had they mimicked this pricing change. Methods: We used quarterly prescription generic drug dispensing data from the IMS-Brogan CompuScript Audit. We used the price per unit in both the pre- and post-policy period and two economics price indexes to estimate the expenditure reduction in Ontario. Further, we used the post-policy Ontario prices to estimate the potential reduction in other provinces. Results: We estimate that total expenditure on generic drugs in Ontario during the second half of 2010 was between $181 and$194 million below what would be expected if prices had remained at pre-policy level. Over half of the reduction in spending was due to savings on just 10 generic ingredients. If other provinces had matched Ontario’s prices, their expenditures over during the latter half of 2010 would have been $445 million lower. Discussion: We found that if Ontario’s pricing scheme were adopted nationally, overall spending on generic drugs in Canada would drop at least$1.28 billion annually—a 5 % decrease in total prescription drug expenditure. Other provinces should seriously consider both changes to their generic drug prices and the use of more competitive bulk purchasing policies

An analysis of the relevance of off-balance sheet items in explaining productivity change in European banking

The 1990s have witnessed a significant growth in bank income generated through non-traditional activities, especially for large EU universal banking institutions. Using the non-parametric Malmquist methodology this study analyses the impact of the inclusion of off-balance sheet (OBS) business in the definition of banks' output when estimating total factor productivity change indexes. Whereas the results reinforce the prevalent view in the recent literature, indicating that the exclusion of non-traditional activities leads to a misspecification of banks' output, the impact of the inclusion of these activities varies. Overall, the inclusion of OBS items results in an increase in estimated productivity levels for all countries under study. However, the impact seems to be the biggest on technological change rather than efficiency change. © 2005 Taylor & Francis

Measuring total factor productivity on Irish dairy farms: a Fisher index approach using farm-level data

peer reviewedThis paper presents a Fisher index measure of the total factor productivity (TFP) performance of Irish dairy farms over the period 2006–2016 using the Teagasc National Farm Survey (NFS) data. The removal of milk quotas in 2015 has led to an increase of over 30% in dairy cow numbers since 2010, and although suckler cow numbers have dropped slightly, the total number of cows in Ireland reached an all-time high of 2.5 million head in 2016. This large increase adds to the environmental pressures attributed to agricultural output and puts the focus firmly on how efficiently the additional agricultural output associated with higher cow numbers is produced. The primary purpose of this paper is to identify a standardised measure of the TFP performance of Irish dairy farms that can be routinely updated using Teagasc NFS data. We found that relative to 2010 the TFP of Irish dairy farms has increased by almost 18%; however, in one production year 2015, when milk quota was removed, the TFP measure increased by 7% and TFP continued to grow by 2.5% in the production year 2016. It would seem therefore that the removal of the European dairy quota system has resulted in a windfall gain for Irish dairy farmers but that productivity gains are continuing. Future data will be required to investigate the longer-term TFP performance of Irish dairy farms in the post-milk quota era

Fish Is Food - The FAO’s Fish Price Index

World food prices hit an all-time high in February 2011 and are still almost two and a half times those of 2000. Although three billion people worldwide use seafood as a key source of animal protein, the Food and Agriculture Organization (FAO) of the United Nations–which compiles prices for other major food categories–has not tracked seafood prices. We fill this gap by developing an index of global seafood prices that can help to understand food crises and may assist in averting them. The fish price index (FPI) relies on trade statistics because seafood is heavily traded internationally, exposing non-traded seafood to price competition from imports and exports. Easily updated trade data can thus proxy for domestic seafood prices that are difficult to observe in many regions and costly to update with global coverage. Calculations of the extent of price competition in different countries support the plausibility of reliance on trade data. Overall, the FPI shows less volatility and fewer price spikes than other food price indices including oils, cereals, and dairy. The FPI generally reflects seafood scarcity, but it can also be separated into indices by production technology, fish species, or region. Splitting FPI into capture fisheries and aquaculture suggests increased scarcity of capture fishery resources in recent years, but also growth in aquaculture that is keeping pace with demand. Regionally, seafood price volatility varies, and some prices are negatively correlated. These patterns hint that regional supply shocks are consequential for seafood prices in spite of the high degree of seafood tradability

Estimation and inference under economic restrictions

Estimation of economic relationships often requires imposition of constraints such as positivity or monotonicity on each observation. Methods to impose such constraints, however, vary depending upon the estimation technique employed. We describe a general methodology to impose (observation-specific) constraints for the class of linear regression estimators using a method known as constraint weighted bootstrapping. While this method has received attention in the nonparametric regression literature, we show how it can be applied for both parametric and nonparametric estimators. A benefit of this method is that imposing numerous constraints simultaneously can be performed seamlessly. We apply this method to Norwegian dairy farm data to estimate both unconstrained and constrained parametric and nonparametric models

Measuring productivity and efficiency: a Kalman filter approach

In the Kalman filter setting, one can model the inefficiency term of the standard stochastic frontier composed error as an unobserved state. In this study a panel data version of the local level model is used for estimating time-varying efficiencies of firms. We apply the Kalman filter to estimate average efficiencies of U.S. airlines and find that the technical efficiency of these carriers did not improve during the period 1999-2009. During this period the industry incurred substantial losses, and the efficiency gains from reorganized networks, code-sharing arrangements, and other best business practices apparently had already been realized