The macroeconomics of price adjustments under information frictions and menu costs

Esta tese se dedica ao estudo de modelos de fixação de preços e suas implicações macroeconômicas. Nos primeiros dois capítulos analiso modelos em que as decisões das firmas sobre seus preços praticados levam em conta custos de menu e de informação. No Capítulo 1 eu estimo tais modelos empregando estatísticas de variações de preços dos Estados Unidos, e concluo que: os custos de informação são significativamente maiores que os custos de menu; os dados claramente favorecem o modelo em que informações sobre condições agregadas são custosas enquanto que as idiossincráticas têm custo zero. No Capítulo 2 investigo as consequências de choques monetários e anúncios de desinflação usando os modelos previamente estimados. Mostro que o grau de não-neutralidade monetária é maior no modelo em que parte da informação é grátis. O Capítulo 3 é um artigo em conjunto com Carlos Carvalho (PUC-Rio) e Antonella Tutino (Federal Reserve Bank of Dallas). No artigo examinamos um modelo de fixação de preços em que firmas estão sujeitas a uma restrição de fluxo de informação do tipo Shannon. Calibramos o modelo e estudamos funções impulso-resposta a choques idiossincráticos e agregados. Mostramos que as firmas vão preferir processar informações agregadas e idiossincráticas conjuntamente ao invés de investigá-las separadamente. Este tipo de processamento gera ajustes de preços mais frequentes, diminuindo a persistência de efeitos reais causados por choques monetários.

Indirect Cost Factors In Menu Pricing

In the discussion - Indirect Cost Factors in Menu Pricing – by David V. Pavesic, Associate Professor, Hotel, Restaurant and Travel Administration at Georgia State University, Associate Professor Pavesic initially states: “Rational pricing methodologies have traditionally employed quantitative factors to mark up food and beverage or food and labor because these costs can be isolated and allocated to specific menu items. There are, however, a number of indirect costs that can influence the price charged because they provide added value to the customer or are affected by supply/demand factors. The author discusses these costs and factors that must be taken into account in pricing decisions. Professor Pavesic offers as a given that menu pricing should cover costs, return a profit, reflect a value for the customer, and in the long run, attract customers and market the establishment. “Prices that are too high will drive customers away, and prices that are too low will sacrifice profit,” Professor Pavesic puts it succinctly. To dovetail with this premise the author provides that although food costs measure markedly into menu pricing, other factors such as equipment utilization, popularity/demand, and marketing are but a few of the parenthetic factors also to be considered. “… there is no single method that can be used to mark up every item on any given restaurant menu. One must employ a combination of methodologies and theories,” says Professor Pavesic. “Therefore, when properly carried out, prices will reflect food cost percentages, individual and/or weighted contribution margins, price points, and desired check averages, as well as factors driven by intuition, competition, and demand.” Additionally, Professor Pavesic wants you to know that value, as opposed to maximizing revenue, should be a primary motivating factor when designing menu pricing. This philosophy does come with certain caveats, and he explains them to you. Generically speaking, Professor Pavesic says, “The market ultimately determines the price one can charge.” But, in fine-tuning that decree he further offers, “Lower prices do not automatically translate into value and bargain in the minds of the customers. Having the lowest prices in your market may not bring customers or profit. “Too often operators engage in price wars through discount promotions and find that profits fall and their image in the marketplace is lowered,” Professor Pavesic warns. In reference to intangibles that influence menu pricing, service is at the top of the list. Ambience, location, amenities, product [i.e. food] presentation, and price elasticity are discussed as well. Be aware of price-value perception; Professor Pavesic explains this concept to you. Professor Pavesic closes with a brief overview of a la carte pricing; its pros and cons.

Modified texture menu analysis

Lower energy and protein intakes are well documented in patients on texture modified diets. In acute hospital settings, the provision of appropriate texture modified foods to meet industry standards is essential for patient safety and nutrition outcomes. The texture modified menu at an acute private hospital was evaluated in accordance with their own nutritional standards (NS) and Australian National Standards (Dietitians Association of Australia and Speech Pathology Australia, 2007). The NS documents portion sizes and nutritional requirements for each menu. Texture B and C menus were analysed qualitatively and quantitatively over 9 days of a 6 day cyclic menu for breakfast (n=4), lunch (n=34) and dinner (n=34). Results indicated a lack of portion control, as specified by the NS, across all meals including breakfast (65–140%), soup (55–115%), meat (45–165%), vegetables (55–185%) and desserts (30–300%). Dilution factors and portion sizes influenced the protein and energy availability of Texture B & C menus. While the Texture B menu provided more energy, neither menu met the NS. Limited dessert options on the Texture C menu restricted the ability of this menu to meet protein NS. A lack of portion control and menu items incorrectly modified can compromise protein and energy intakes. Strategies to correct serving sizes and provision of alternate protein sources were recommended. Suggestions included cost-effectively increasing the variety of foods to assist protein and energy intake and the procurement of standardised equipment and visual aids to assist food preparation and presentation in accordance with texture modified guidelines and the NS.

Menu Engineering: A Model Including Labor

Menu engineering is a methodology to classify menu items by their contribution margin and popularity. The process discounts the importance of food cost percentage, recognizing that operators deposit cash, not percentages. The authors raise the issue that strict application of the principles of menu engineering may result in an erroneous evaluation of a menu item, and also may be of little use without considering the variable portion of labor. They describe an enhancement to the process by considering labor.

Reducing the global burden of depression : population level analysis of intervention cost-effectiveness in 14 world regions

International evidence on the cost and effects of interventions for reducing the global burden of depression remain scarce. Aims: To estimate the population-level cost-effectiveness of evidence-based depression interventions and their contribution towards reducing current burden. Method: Primary-care-based depression interventions were modelled at the level of whole populations in 14 epidemiological subregions of the world. Total population-level costs (in international dollars or I$) and effectiveness (disability adjusted life years (DALYs) averted) were combined to form average and incremental cost-effectiveness ratios. Results: Evaluated interventions have the potential to reduce the current burden of depression by 10–30%. Pharmacotherapy with older antidepressant drugs, with or without proactive collaborative care, are currently more cost-effective strategies than those using newer antidepressants, particularly in lower-income subregions. Conclusions: Even in resource-poor regions, each DALYaverted by efficient depression treatments in primary care costs less than 1 year of average per capita income, making such interventions a cost-effective use of health resources. However, current levels of burden can only be reduced significantlyif there is a substantialincrease substantial increase intreatment coverage.

Correcting for bias when estimating the cost of hospital-acquired infection : an analysis of lower respiratory tract infections in non-surgical patients

Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).