Can sentiment surveys pre-empt real estate market activities?

We evaluate a number of real estate sentiment indices to ascertain current and forward-looking information content that may be useful for forecasting the demand and supply activities. Our focus lies on sector-specific surveys targeting the players from the supply-side of both residential and non-residential real estate markets. Analyzing the dynamic relationships within a Vector Auto-Regression (VAR) framework, we test the efficacy of these indices by comparing them with other coincident indicators in predicting real estate returns. Overall, our analysis suggests that sentiment indicators convey important information which should be embedded in the modeling exercise to predict real estate market returns. Generally, sentiment indices show better information content than broad economic indicators. The goodness of fit of our models is higher for the residential market than for the non-residential real estate sector. The impulse responses, in general, conform to our theoretical expectations. Variance decompositions and out-of-sample predictions generally show desired contribution and reasonable improvement respectively, thus upholding our hypothesis. Quite remarkably, consistent with the theory, the predictability swings when we look through different phases of the cycle. This perhaps suggests that, e.g. during recessions, market players’ expectations may be more accurate predictor of the future performances, conceivably indicating a ‘negative’ information processing bias and thus conforming to the precautionary motive of consumer behaviour.

Participatory rural appraisal of dairy farms in the north west province of Cameroon

A Participatory Rural Appraisal (PRA) was conducted in dairy farms of the North West Province of Cameroon. The aim of the PRA was to have a better understanding of the prevailing dairy systems, identify problems, and set priorities for research and development that can contribute to improved systems of production. A multidisciplinary team of researchers and extension agents was constituted. It was made up of scientists of the following fields: cattle management, forage science, agro economy, veterinary, dairy technology, nutrition and extension. The research team visited farmers' groups and divided itself into subgroups for farm and village walks during which direct observations were also noted. The extension agent of the locality, key informants, gave additional information overlooked by farmers. Interviews were also carried out with other stakeholders of the dairy sector. The research team met the day following the visit to agree on a common report. Results show that five small scale dairy production systems are found in the region: transhumance, improved extensive, semi intensive, zero grazing and peri-urban. Agriculture is well integrated to dairying. Main constraints include in order of importance: poor marketing opportunities and long distances to market, limited grazing land and poor supplementation strategies, poor reproductive management and poor calving interval, inadequate knowledge in processing, hygiene and milk preservation, and limited health control. In market oriented farms, reproduction and feeding were the most important constraints. Main factors influencing dairy production are: milk collection, fresh milk price, consumer demand, genotype and management. These results suggest that much can be done to improve production by extending improved packages to dairy farmers.

Expert judgement in the processes of commercial property market forecasting

In this paper, we investigate the role of judgement in the formation of forecasts in commercial property markets. The investigation is based on interview surveys with the majority of UK forecast producers, who are using a range of inputs and data sets to form models to predict an array of variables for a range of locations. The findings suggest that forecasts need to be acceptable to their users (and purchasers) and consequently forecasters generally have incentives to avoid presenting contentious or conspicuous forecasts. Where extreme forecasts are generated by a model, forecasters often engage in ‘self‐censorship’ or are ‘censored’ following in‐house consultation. It is concluded that the forecasting process is significantly more complex than merely carrying out econometric modelling, forecasts are mediated and contested within organisations and that impacts can vary considerably across different organizational contexts.

Expert judgement in the processes of commercial property market forecasting

In this paper we investigate the role of judgement in the formation of forecasts in commercial real estate markets. Based on interview surveys with the majority of forecast producers, we find that real estate forecasters are using a range of inputs and data sets to form models to predict an array of variables for a range of locations. The findings suggest that forecasts need to be acceptable to their users (and purchasers) and consequently forecasters generally have incentives to avoid presenting contentious or conspicuous forecasts. Where extreme forecasts are generated by a model, forecasters often engage in ‘self-censorship’ or are ‘censored’ following in-house consultation. It is concluded that the forecasting process is more complex than merely carrying out econometric modelling and that the impact of the influences within this process vary considerably across different organizational contexts.