Micro Foundations of Price-Setting Behaviour: Evidence from Canadian Firms

How do firms adjust prices in the marketplace? Do they tend to adjust prices infrequently in response to changes in market conditions? If so, why? These remain key questions in macroeconomics, particularly for central banks that work to keep inflation low and stable. The authors use the Bank of Canada's 2002-03 price-setting survey data to investigate Canadian firms' price-setting behaviour; they also analyze the micro foundations for the firms' pricing behaviour using count data and probit models. The authors find that, all else being equal, firms tend to adjust prices more frequently if they are state-dependent price-setters, operate in the trade sector, or have large variable costs or more direct competitors. There are various sticky-price theories; in the Bank's price-setting survey, the senior management of firms were read a simple statement in non-technical language that paraphrased each sticky-price theory, and were then asked whether the statement applied to their firm. The most frequently recognized sticky-price theories are customer relations, cost-based pricing, and coordination failure. The authors' analysis indicates that if firms recognize coordination failure on price increases, sticky information, menu costs, factor stability, or customer relations as being important, they tend to adjust prices less frequently. The authors also find that the patterns discernible within firms' recognition of stickyprice theories are strongly associated with firms' micro foundations.Inflation and prices; Transmission of monetary policy

Insolvency and Economic Development: Regional Variation and Adjustment

This paper examines the determinants of the rate of forced insolvency in New Zealand. The study incorporates two key features. First, we use regional as well as national data to explain insolvencies. The data cover six regions which have had a variety of economic experiences over the sample period (1988-2003). Second, we explain the total rate of forced insolvency in New Zealand, including both personal bankruptcies and involuntary company liquidations. We find that increases in regional economic activity and regional property values (the latter representing collateral effects) reduce regional insolvencies. An increase in credit provision (increased leverage) raises the rate of insolvencies. In a low-inflation environment, a rise in the inflation rate reduces insolvencies, but this effect disappears in a high-inflation environment. We show that interactions between economic activity, leverage and property price shocks provide a rich understanding of how region-specific shocks can compound into significant localised economic cycles.Insolvency; liquidation; bankruptcy; collateral; regional economy

Insolvency and Economic Development:Regional Variation and Adjustment

This paper examines the determinants of the rate of forced insolvency in New Zealand. The study incorporates two key features. First, we use regional as well as national data to explain insolvencies. The data cover six regions which have had a variety of economic experiences over the sample period (1988–2003). Second, we explain the total rate of forced insolvency in New Zealand, including both personal bankruptcies and involuntary company liquidations. We find that increases in regional economic activity and regional property values (the latter representing collateral effects) reduce regional insolvencies. An increase in credit provision (increased leverage) raises the rate of insolvencies. In a low-inflation environment, a rise in the inflation rate reduces insolvencies, but this effect disappears in a high-inflation environment. We show that interactions between economic activity, leverage and property price shocks provide a rich understanding of how region-specific shocks can compound into significant localised economic cycles.Insolvency; liquidation; bankruptcy; collateral; regional economy

Highway Infrastructure Investment and Regional Employment Growth: Dynamic Panel Regression Analysis

A number of macro-level studies attempting to establish the statistical link between public investment in highway infrastructure and employment have applied econometric techniques to estimate the effect of highways while controlling for the effects associated with other factors. Unfortunately, direct use of empirical findings from these historic and recent studies, in shaping transport policy and supporting particular investment decisions, has been rather limited by mixed and inconclusive evidence in the literature. Apart from the common differences among these studies in scope and methodology, another possible reason for the contradictory evidence is that much of the previous work has generally suffered from several methodology drawbacks. In many studies, for instance, several important determinants of employment growth are omitted, and the choices of control variables included in the estimated equations generally are not based on theory. Those studies based solely on cross-sectional data also typically do not account for unobserved regional heterogeneity that may explain spatial differences in employment changes. Moreover, the possibility that the causal relationship between transportation investment and economic growth could work in both directions is generally ignored. This paper attempts to shed some light on this controversy by analysing the effect of highway investment on county-level employment in the State of North Carolina, United States. We derive a reduced from model of equilibrium employment that considers the effects of highways and other potential factors on the supply and demand for labour. Given the potential for lagged responses of the labour market to any exogenous shock, we assume a partial adjustment process for actual employment in our empirical model. A panel data set for 100 North Carolina counties from 1985 to 1997 is used in order to control for unobserved county and time specific effects using panel regression techniques. We also address the causality issue by the use of a two-stage least squares procedure with an instrumental variable. Our main results are that the employment effect of highway infrastructure depends critically on model specifications considered, and failure to account for the dynamics of employment adjustment could lead to an upward bias in the estimated effect of highways.

Methodological and empirical challenges in modelling residential location choices

The modelling of residential locations is a key element in land use and transport planning. There are significant empirical and methodological challenges inherent in such modelling, however, despite recent advances both in the availability of spatial datasets and in computational and choice modelling techniques. One of the most important of these challenges concerns spatial aggregation. The housing market is characterised by the fact that it offers spatially and functionally heterogeneous products; as a result, if residential alternatives are represented as aggregated spatial units (as in conventional residential location models), the variability of dwelling attributes is lost, which may limit the predictive ability and policy sensitivity of the model. This thesis presents a modelling framework for residential location choice that addresses three key challenges: (i) the development of models at the dwelling-unit level, (ii) the treatment of spatial structure effects in such dwelling-unit level models, and (iii) problems associated with estimation in such modelling frameworks in the absence of disaggregated dwelling unit supply data. The proposed framework is applied to the residential location choice context in London. Another important challenge in the modelling of residential locations is the choice set formation problem. Most models of residential location choices have been developed based on the assumption that households consider all available alternatives when they are making location choices. Due the high search costs associated with the housing market, however, and the limited capacity of households to process information, the validity of this assumption has been an on-going debate among researchers. There have been some attempts in the literature to incorporate the cognitive capacities of households within discrete choice models of residential location: for instance, by modelling households’ choice sets exogenously based on simplifying assumptions regarding their spatial search behaviour (e.g., an anchor-based search strategy) and their characteristics. By undertaking an empirical comparison of alternative models within the context of residential location choice in the Greater London area this thesis investigates the feasibility and practicality of applying deterministic choice set formation approaches to capture the underlying search process of households. The thesis also investigates the uncertainty of choice sets in residential location choice modelling and proposes a simplified probabilistic choice set formation approach to model choice sets and choices simultaneously. The dwelling-level modelling framework proposed in this research is practice-ready and can be used to estimate residential location choice models at the level of dwelling units without requiring independent and disaggregated dwelling supply data. The empirical comparison of alternative exogenous choice set formation approaches provides a guideline for modellers and land use planners to avoid inappropriate choice set formation approaches in practice. Finally, the proposed simplified choice set formation model can be applied to model the behaviour of households in online real estate environments.Open Acces

Rural demand for drought insurance

Many agricultural regions in the developing world are subject to severe droughts, which can have devastating effects on household incomes and consumption, especially for the poor. To protect consumption, rural households engage in many different risk management strategies - some mainly risk-reducing and some simply coping devices to protect consumption once income has been lost. An important limitation of these traditional risk management strategies is their inability to insure against covariate risks and they are also costly.. The absence of formal credit and insurance institutions, which offer an efficient alternative by overcoming regional covariance problems and reducing the cost of risk management, amounts to a market failure. Past research has paid much more attention to the supply-side reasons for this market failure than to the demand side question of whether there exist financial instruments that farmers want and would be willing to pay for. The authors use a dynamic household model to examine the efficiency of drought management strategies used by peasant households. An attractive feature of the method is that it exploits actual production (input-output) data and does not deal with the usually unreliable data on household consumption and leisure activities. The model is applied to a two-year panel of data on households from five villages in Tamil Nadu (South India). The sample is small, but the data are special, as one of the two years was a severe drought year. The results indicate that agricultural households exhibit significant risk-avoidance bahavior, and that even though they may use a range of risk management strategies, there still remains an unmet demand for insurance against drought risks. The study did not estimate the likely costs of supplying drought insurance, but the latent demand in the study region is strong enough to more than cover the breakeven rate of approximately the pure risk cost (the probability of drought) plus 5 percent administration costs. The findings confirm the inadequacies of traditional strategies of coping with droughts in poor rural areas. Because of the catastrophic and simultaneous effects of droughts on all households over large areas, there is limited scope for spreading risks effectively at the local level. Either households must increase their savings significantly (a problem with low average incomes and an absence of safe and convenient savings instruments), or more effective risk management aids are needed that can overcome the covariation problem. Improved financial markets (with both credit and savings facilities) could be helpful, particularly if they intermediate over a larger and more diverse economic base than the local economy. Alternatively, formal drought insurance in the form of a drought (or rainfall) lottery might be feasible, and the results suggest that it could be sold on a full-cost basis.Environmental Economics&Policies,Economic Theory&Research,Banks&Banking Reform,Services&Transfers to Poor,Safety Nets and Transfers

Adoption and Abandonment of Organic Farming: An Empirical Investigation of the Irish Drystock Sector

The adoption and possible abandonment of organic farming has yet received little attention in the literature. As time plays an important role in explaining farming decisions, a dynamic econometric framework, namely duration analysis, is used. The probability of entry to and exit of the organic drystock sector is modeled considering a wide range of economic and non‐economic factors. Organic support payments emerge as important driving factor of adoption over time. The empirical results also highlight the importance of environmental and risk attitudes, farming experience as well as influence of other organic farmers on the probability to adopt organic farming; whereas decisions to abandon organic farming appear to be mainly driven by economic and structural factors. Farmers who have an off‐farm job are more likely to abandon organic farming and a more ‘intensive’ farm system has a positive effect on staying organic.adoption, abandonment, organic farming, duration analysis, economic and non‐economic factors., Farm Management,

Seismic Risk Analysis of Revenue Losses, Gross Regional Product and transportation systems.

Natural threats like earthquakes, hurricanes or tsunamis have shown seri- ous impacts on communities. In the past, major earthquakes in the United States like Loma Prieta 1989, Northridge 1994, or recent events in Italy like L’Aquila 2009 or Emilia 2012 earthquake emphasized the importance of pre- paredness and awareness to reduce social impacts. Earthquakes impacted businesses and dramatically reduced the gross regional product. Seismic Hazard is traditionally assessed using Probabilistic Seismic Hazard Anal- ysis (PSHA). PSHA well represents the hazard at a specific location, but it’s unsatisfactory for spatially distributed systems. Scenario earthquakes overcome the problem representing the actual distribution of shaking over a spatially distributed system. The performance of distributed productive systems during the recovery process needs to be explored. Scenario earthquakes have been used to assess the risk in bridge networks and the social losses in terms of gross regional product reduction. The proposed method for scenario earthquakes has been applied to a real case study: Treviso, a city in the North East of Italy. The proposed method for scenario earthquakes requires three models: one representation of the sources (Italian Seismogenic Zonation 9), one attenuation relationship (Sa- betta and Pugliese 1996) and a model of the occurrence rate of magnitudes (Gutenberg Richter). A methodology has been proposed to reduce thou- sands of scenarios to a subset consistent with the hazard at each location. Earthquake scenarios, along with Mote Carlo method, have been used to simulate business damage. The response of business facilities to earthquake has been obtained from fragility curves for precast industrial building. Fur- thermore, from business damage the reduction of productivity has been simulated using economic data from the National statistical service and a proposed piecewise “loss of functionality model”. To simulate the economic process in the time domain, an innovative businesses recovery function has been proposed. The proposed method has been applied to generate scenarios earthquakes at the location of bridges and business areas. The proposed selection method- ology has been applied to reduce 8000 scenarios to a subset of 60. Subse- quently, these scenario earthquakes have been used to calculate three system performance parameters: the risk in transportation networks, the risk in terms of business damage and the losses of gross regional product. A novel model for business recovery process has been tested. The proposed model has been used to represent the business recovery process and simulate the effects of government aids allocated for reconstruction. The proposed method has efficiently modeled the seismic hazard using scenario earthquakes. The scenario earthquakes presented have been used to assess possible consequences of earthquakes in seismic prone zones and to increase the preparedness. Scenario earthquakes have been used to sim- ulate the effects to economy of the impacted area; a significant Gross Regional Product reduction has been shown, up to 77% with an earthquake with 0.0003 probability of occurrence. The results showed that limited funds available after the disaster can be distributed in a more efficient way

Impact of New Madrid Seismic Zone Earthquakes on the Central USA, Vol. 1 and 2

The information presented in this report has been developed to support the Catastrophic Earthquake Planning Scenario workshops held by the Federal Emergency Management Agency. Four FEMA Regions (Regions IV, V, VI and VII) were involved in the New Madrid Seismic Zone (NMSZ) scenario workshops. The four FEMA Regions include eight states, namely Illinois, Indiana, Kentucky, Tennessee, Alabama, Mississippi, Arkansas and Missouri. The earthquake impact assessment presented hereafter employs an analysis methodology comprising three major components: hazard, inventory and fragility (or vulnerability). The hazard characterizes not only the shaking of the ground but also the consequential transient and permanent deformation of the ground due to strong ground shaking as well as fire and flooding. The inventory comprises all assets in a specific region, including the built environment and population data. Fragility or vulnerability functions relate the severity of shaking to the likelihood of reaching or exceeding damage states (light, moderate, extensive and near-collapse, for example). Social impact models are also included and employ physical infrastructure damage results to estimate the effects on exposed communities. Whereas the modeling software packages used (HAZUS MR3; FEMA, 2008; and MAEviz, Mid-America Earthquake Center, 2008) provide default values for all of the above, most of these default values were replaced by components of traceable provenance and higher reliability than the default data, as described below. The hazard employed in this investigation includes ground shaking for a single scenario event representing the rupture of all three New Madrid fault segments. The NMSZ consists of three fault segments: the northeast segment, the reelfoot thrust or central segment, and the southwest segment. Each segment is assumed to generate a deterministic magnitude 7.7 (Mw7.7) earthquake caused by a rupture over the entire length of the segment. US Geological Survey (USGS) approved the employed magnitude and hazard approach. The combined rupture of all three segments simultaneously is designed to approximate the sequential rupture of all three segments over time. The magnitude of Mw7.7 is retained for the combined rupture. Full liquefaction susceptibility maps for the entire region have been developed and are used in this study. Inventory is enhanced through the use of the Homeland Security Infrastructure Program (HSIP) 2007 and 2008 Gold Datasets (NGA Office of America, 2007). These datasets contain various types of critical infrastructure that are key inventory components for earthquake impact assessment. Transportation and utility facility inventories are improved while regional natural gas and oil pipelines are added to the inventory, alongside high potential loss facility inventories. The National Bridge Inventory (NBI, 2008) and other state and independent data sources are utilized to improve the inventory. New fragility functions derived by the MAE Center are employed in this study for both buildings and bridges providing more regionally-applicable estimations of damage for these infrastructure components. Default fragility values are used to determine damage likelihoods for all other infrastructure components. The study reports new analysis using MAE Center-developed transportation network flow models that estimate changes in traffic flow and travel time due to earthquake damage. Utility network modeling was also undertaken to provide damage estimates for facilities and pipelines. An approximate flood risk model was assembled to identify areas that are likely to be flooded as a result of dam or levee failure. Social vulnerability identifies portions of the eight-state study region that are especially vulnerable due to various factors such as age, income, disability, and language proficiency. Social impact models include estimates of displaced and shelter-seeking populations as well as commodities and medical requirements. Lastly, search and rescue requirements quantify the number of teams and personnel required to clear debris and search for trapped victims. The results indicate that Tennessee, Arkansas, and Missouri are most severely impacted. Illinois and Kentucky are also impacted, though not as severely as the previous three states. Nearly 715,000 buildings are damaged in the eight-state study region. About 42,000 search and rescue personnel working in 1,500 teams are required to respond to the earthquakes. Damage to critical infrastructure (essential facilities, transportation and utility lifelines) is substantial in the 140 impacted counties near the rupture zone, including 3,500 damaged bridges and nearly 425,000 breaks and leaks to both local and interstate pipelines. Approximately 2.6 million households are without power after the earthquake. Nearly 86,000 injuries and fatalities result from damage to infrastructure. Nearly 130 hospitals are damaged and most are located in the impacted counties near the rupture zone. There is extensive damage and substantial travel delays in both Memphis, Tennessee, and St. Louis, Missouri, thus hampering search and rescue as well as evacuation. Moreover roughly 15 major bridges are unusable. Three days after the earthquake, 7.2 million people are still displaced and 2 million people seek temporary shelter. Direct economic losses for the eight states total nearly $300 billion, while indirect losses may be at least twice this amount. The contents of this report provide the various assumptions used to arrive at the impact estimates, detailed background on the above quantitative consequences, and a breakdown of the figures per sector at the FEMA region and state levels. The information is presented in a manner suitable for personnel and agencies responsible for establishing response plans based on likely impacts of plausible earthquakes in the central USA.Armu W0132T-06-02unpublishednot peer reviewe

INFORMATION AND THE ADOPTION OF PRECISION FARMING

This study examines the relationship between precision farming information sources and precision farming adoption. The analysis accounts for the fact that not all farmers are aware of precision farming techniques and that those who are aware may not be a random sample. Results indicate that many information sources increase adoption relative to information only from the media, but contact with crop consultants has had the greatest impact on the adoption of precision farming technologies.Farm Management,