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This paper studies the forecasting ability of various Phillips curve specifications for 1 year ahead headline and underlying core inflation measures for three open currently inflation targeting (IT) countries: Sweden, Canada and New Zealand. The changes of the monetary policy regime in these countries are discussed for periods of fixed exchange rate regime, early years of IT and later periods in the light of inflation forecasting accuracy. The paper finds evidence that Phillips curve models can improve inflation forecasts against the random walk benchmark in the periods when the central bank is explicitly targeting the inflation. Yet, the results from earlier periods indicate heterogeneity in individual model performance across various econometric specifications and different sample periods. [ABSTRACT FROM AUTHOR]

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Objectives: Weather is a key source of marine risk, but relationships between fishing activity, safety, and weather remain poorly understood. Critically, the fit between available marine forecast products, fish harvesters' needs, and harvester's decision-making processes has not been rigorously assessed. This paper addresses these gaps by documenting a) weather-related decision-making by harvesters, and its relationship to forecasts across multiple regions and fisheries on Canada's East coast (Newfoundland) and b) the dynamics of forecast production priorities. Methods: A multi-disciplinary, community-engaged research approach, conducted in partnership with the Newfoundland and Labrador Fish Harvesting Safety Association (NL-FHSA). Data consist of semi-structured interviews with fish harvesters and weather forecasters, focused on marine forecast production and use. Results: Results emphasize that there is a subjective "art" to both production and use of marine forecasts. Forecasters and harvesters share several common values regarding forecasts, but different emphases: forecasters favor some combination of accuracy, consistency, and utility, while harvesters are largely concerned with utility. Finally, harvesters' decision-making is based on nuanced and contextual interpretations of a few key hazards (winds and, to a lesser extent, waves). Conclusion: This community-engaged research has triggered experimentation with forecasts tailored to fisheries utility within Environment and Climate Change Canada (ECCC). It lays the groundwork for ongoing, mutually beneficial dialogue between forecasters and harvesters, engaging harvesters with the forecasting process while familiarizing forecasters with harvester's decision-making processes. Ongoing industry partnerships (NL-FHSA) continue to sustain momentum from this study towards further enhancing the utility of future marine forecasts for small-scale harvesters. [ABSTRACT FROM AUTHOR]

Autoregressive Integrated Moving Average (ARIMA) models have been widely used to forecast and model the development of various infectious diseases including COVID-19 outbreaks; however, such use of ARIMA models does not respect the count nature of the pandemic development data. For example, the daily COVID-19 death count series data for Canada and the United States (USA) are generally skewed with lots of low counts. In addition, there are generally waved patterns with turning points influenced by government major interventions against the spread of COVID-19 during different periods and seasons. In this study, we propose a novel combination of the segmented Poisson model and ARIMA models to handle these features and correlation structures in a two-stage process. The first stage of this process is a generalization of trend analysis of time series data. Our approach is illustrated with forecasting and modeling of daily COVID-19 death count series data for Canada and the USA. [ABSTRACT FROM AUTHOR]

An inaccurate forecast of inflation is costlier to economic agents when the inflation rate is high and volatile. In this situation, the use of more sophisticated and information-oriented forecasting models become economically efficient. We test this hypothesis by analysing the forecasting accuracy of vector auto-regressive (VAR), auto-regressive integrated moving average (ARIMA) and static expectation models. We use Canadian data and divide the post-sample forecasting period into four sub-periods, based on high/low and volatile/stable inflation. Prediction errors are compared for both short-term and long-term forecasts. Finally, the paper proposes a portfolio approach for obtaining a more accurate forecast of inflation. [ABSTRACT FROM AUTHOR]

Autoregressive (AR) models are useful in time series analysis. Inferences under such models are distorted in the presence of measurement error, a common feature in applications. In this article, we establish analytical results for quantifying the biases of the parameter estimation in AR models if the measurement error effects are neglected. We consider two measurement error models to describe different data contamination scenarios. We propose an estimating equation approach to estimate the AR model parameters with measurement error effects accounted for. We further discuss forecasting using the proposed method. Our work is inspired by COVID-19 data, which are error-contaminated due to multiple reasons including those related to asymptomatic cases and varying incubation periods. We implement the proposed method by conducting sensitivity analyses and forecasting the fatality rate of COVID-19 over time for the four most populated provinces in Canada. The results suggest that incorporating or not incorporating measurement error effects may yield rather different results for parameter estimation and forecasting. [ABSTRACT FROM AUTHOR]

This research explores the use of hypothetical discussion – content that is speculative, conjectural, or abstract – in newspaper articles containing migrant crime. Content analysis and logistic regression are used to examine the presence of hypothetical discussion and its associated content in 225 newspaper articles from Canada, the UK, and the US. Results include various positive predictors of hypothetical discussion – e.g., mention of Islam; irregular migration status – as well as negative predictors – e.g., crime or migration status used in the article headline. Discussion of results are presented in the context of recent migration crises and growing nationalism. [ABSTRACT FROM AUTHOR]

This paper has investigated the forecasting performance of MDA business failure prediction models developed by Altman (1968) and Springate (1978) using Canadian data. It has sought to ascertain the degree to which these models have been used in Canada. In addition, the models' forecasting accuracy was tested against that of a group of Canadian bankers. The empirical analysis has used data taken from the active files of a large Canadian bank. The data included the latest three years' financial statements for 20 unsatisfactory borrowing accounts and 20 satisfactory borrowing accounts over the 1979-82 period. The results obtained suggest that, while Altman's model is somewhat known among Canadian banks, none of the indigenous banks is currently using the model and only one is conducting a feasibility study to determine the benefits of implementing it. We also found that both Altman and Springate models were poor predictors of unsatisfactory borrowing accounts two (50%) and three (29%) years before the fact. Finally, one of the most interesting results obtained is the inability of MDA bankruptcy prediction models to outperform Canadian bankers' predictive ability. Bankers' predictions were derived from a limited information set (financial statements and univariate financial ratios). [ABSTRACT FROM AUTHOR]

The complex pattern of gold production in Canada, which differs from the classic Hubbert´s curve, is modeled, and a short-term forecast is made, via the Fundamental Equation of Mineral Production (FEMP). For intervals of time with a variable production to reserves ratio, a discrete piecewise version of the equation updates the reserves and the Production to Reserves Ratio (PRR) by units of time. These piecewise linear portions of the PRR correspond to sub-cycles of rising and declining production embedded in the overall history of production. This version of the FEMP allows modelling of any pattern of mineral production at a universal range of scales. The Hubbert´s linearization indicates the official account of reserves underestimates the real amount of gold resources in Canada. The equivalence between the Hubbert's formula and the FEMP is introduced. The Hubbert curve is shown as a case study of the Fundamental Equation, featured as the product of a quadratic function of the cumulative production and a rational function of the PRR with time. The forecast for Canada's current gold production illustrates the metal output is about to peak with an all-time record high in the near future, unless new findings or influential global economic factors are introduced (i.e., a sharp and sustained growth of gold demand from regional markets), allowing an increase of the slope of the linear function featured by the PRR of the FEMP-based model. [ABSTRACT FROM AUTHOR]

During takeover battles, a tender offer provides a call option right to the target’s shareholders: it guarantees the offered price but maintains the chance of a higher offer. We present an options-based approach to estimate the probability and expected value of higher competing takeover bids using target stock price data. Analysing Canadian takeover battles in the period 1997 to 2007 we find that during the 5 trading days prior to the occurrence of an increased takeover bid, the estimated probability of a higher bid exceeds 80% on average and the expected value of a potential competing bid almost matches the realized value. [ABSTRACT FROM PUBLISHER]

This article evaluates how consistently reliable the information content of individual financial variables is for Canada's future output growth. We estimate the timing of structural changes in linear growth models and check robustness to specification changes, multiple breaks, and business cycle asymmetry. Our simulated out-of-sample forecast evaluation strategy, using the Mean Square Error F-type (MSE-F) and the new encompassing (ENC-NEW) tests, shows that the leading information content of most financial variables for Canada's future Gross Domestic Product (GDP) growth has deteriorated substantially after 1984:04, but the 1–3-year term spread exhibits a consistently reliable predictive ability at the 1 and 2 quarter horizons and has significant forecasting ability at the 8 quarter horizon. Also, the real M1 money growth has regained its ability to forecast output growth since 1991:01. [ABSTRACT FROM AUTHOR]