Forecasting inflation with consumer survey data – application of multi-group confirmatory factor analysis to elimination of the general sentiment factor

This paper (1) examines the properties of survey based households’ inflation expectations and investigates their forecasting performance. With application of the individual data from the State of the Households’ Survey (50 quarters between 1997Q4 and 2010Q1) it was shown that inflation expectations were affected by the consumer sentiment. Multi-Group Confirmatory Factor Analysis (MGCFA) was employed to verify whether a set of proxies provides a reliable basis for measurement of two latent phenomena – consumer sentiment and inflation expectations. Following the steps proposed by Davidov (2008) and Steenkamp and Baumgartner (1998), it appeared that it was possible to specify and estimate a MGCFA model with partial measurement invariance. Thus it was possible to eliminate the influence of consumer sentiment on inflation expectations and at the same time to obtain individually corrected answers concerning the inflation expectations. Additionally, it was shown that the linear relation between consumer sentiment and inflation expectations was stable over time. As a by-product of analysis, it was possible to show that respondents during the financial crisis were much less consistent in their answers to the questions of the consumer questionnaire. In the next step of the analysis, data on inflation expectations were applied to modelling and forecasting inflation. It was shown that with respect to standard ARIMA processes, inclusion of the information on the inflation expectations significantly improved the in-sample and out-of-sample forecasting performance of the time-series models. Especially out-of-sample performance was significantly better as the average absolute error in forecasts of headline and core inflation was reduced by half. It was also shown that models with inflation expectations based on the CFA method (after elimination of the consumer sentiment factor) provided better in-sample forecasts of inflation. Nevertheless, it was not confirmed for the out-of-sample forecasts. (1) Project financed by the National Bank of Poland. Polish title of the project: "Prognozowanie inflacji na podstawie danych koniunktury gospodarstw domowych. Zastosowanie konfirmacyjnej analizy czynnikowej dla wielu grup do oczyszczenia prognoz inflacji z czynnika ogólnego nastroju gospodarczego."Inflation expectations, Inflation forecasts, Confirmatory Factor Analysis

Do all savings matter equally? : saving types and emotional well ‑being among older adults : evidence from panel data.

Ill-being and mental ill-health have been on the rise in both Europe and the United States, especially among middle-aged and older adults. Although financial security has been shown to play a protective role in emotional well-being, little is known about the protective role of different types of family assets on mental health and well-being. Using longitudinal survey data from the Survey of Health, Aging and Retirement in Europe (SHARE) collected between 2004 and 2017, we examined the role of different types of family assets in emotional well-being and depression. A multivariate proportional hazard model with time-varying covariates was used. We found that family assets may play a significant protective role against depression, loneliness, and a decreased quality of life. Different forms of family assets may play diverse roles in protecting against the risks of ill-being and mental ill-health; however, their roles in increasing the chances of overcoming ill-being are less pronounced. Promotion of saving behaviours and proper financial management can help protect against adverse well-being and health outcomes in middle-aged and older adults. Keyword

Bayesowskie uśrednianie klasycznych oszacowań w prognozowaniu wskaźników makroekonomicznych z użyciem danych z testów koniunktury

This paper presents another version of model designed to forecast main macroeconomic indicators with the use of economic survey data. In previous papers (Białowolski, Kuszewski, Witkowski, 2010a, 2010b, 2011, 2012a, 2012b) methods for developing models used for forecasting GDP growth rate, unemployment rate and CPI were proposed. The set of regressors in those models included only lagged dependent variables and indices based on various survey data. In this paper the specification of the forecasting model is selected with the use of Bayesian averaging of classical estimates (BACE). This algorithm enables an automatic process of selection of functional form of the model. Next the influence of deterministic and stochastic seasonality in time series on forecasting process is concerned. An intuitive procedure of applying and selecting among both types of seasonality in the forecasting process is discussed. Afterwards their forecasting capabilities are considered. (original abstract)W niniejszej pracy przedstawiono kolejną wersję modelu dla prognozowania podstawowych wskaźników makroekonomicznych z wykorzystaniem danych z testów koniunktury. W pracach Białowolskiego, Kuszewskiego i Witkowskiego (2010a, 2010b, 2011, 2012a, 2012b) rozwijano metodykę budowy modeli dla prognozowania tempa zmian produktu krajowego brutto, stopy bezrobocia i wskaźnika cen towarów konsumpcyjnych. W zbiorze regresorów tych modeli, oprócz opóźnionych w czasie zmiennych endogenicznych, uwzględnia się wyłącznie wyniki różnych testów koniunktury. Badanie dotyczy specyfikacji modelu prognostycznego metodą bayesowskiego uśredniania klasycznych oszacowań (Bayesian averaging of classical estimates, BACE). Przyjęte rozwiązanie umożliwia automatyzację proces doboru postaci modelu. W kolejnym etapie postępowania jest rozważany wpływ sezonowości deterministycznej i stochastycznej szeregów czasowych na wynik procesu prognozowania. Zaproponowano intuicyjną procedurę uwzględniania obu rodzajów sezonowości w procesie prognozowania. Po zakończeniu procesu estymacji i doboru modeli weryfikowano ich możliwości prognostyczne. (abstrakt oryginalny

Psychological caring climate at work, mental health, well-being, and work-related outcomes : evidence from a longitudinal study and health insurance data

Psychological climate for caring (PCC) is a psychosocial factor associated with individual work outcomes and employee well-being. Evidence on the impacts of various psychological climates at work is based mostly on self-reported health measures and cross-sectional data. We provide longitudinal evidence on the associations of PCC with subsequent diagnosed depression and anxiety, subjective well-being, and self-reported work outcomes. Employees of a US organization with a worker well-being program provided data for the analysis. Longitudinal survey data merged with data from personnel files and health insurance claims records comprising medical information on diagnosis of depression and anxiety were used to regress each outcome on PCC at baseline, adjusting for prior values of all outcomes and other covariates. PCC was found to be associated with lower odds of subsequent diagnosed depression, an increase in overall well-being, mental health, physical health, social connectedness, and financial security, as well as a decrease in distraction at work, an increase in productivity/engagement and possibly in job satisfaction. There was little evidence of associations between PCC and subsequent diagnosed anxiety, character strengths, and work-family conflict. Work policies focused on improving PCC may create a promising pathway to promoting employee health and well-being as well as improving work-related outcomes

Analiza formułowania ocen i prognoz przez gospodarstwa domowe z wykorzystaniem modelowania równań strukturalnych

In this paper, an issue of interdependence between the responses of respondents in the State of the Households survey in Poland was investigated. Four areas were proposed in which respondents provide answers to the questionnaire: current situation of the household (CHS), current situation of the economy (CES), forecasted situationof the household (FSH) and forecasted economic situation (FSE). For each of the areas with application of the multi-group confirmatory factor analysis a measurement model was estimated. It was shown that for three of the four areas (except CHS) it is possible to select a set of questions measuring consistently analyzed area. For CHS a single question indicator describing the area was proposed. In the following step a structural model was estimated. Thus it was possible to verify the relationships between latent variables (areas). It was shown that households responses to questions concerning FSH are interrelated with responses in each of the other three areas. Strong interdependence between individual respondents' answers in the areas of (1) CES and FSE, but also (2) CES and CHS was identified. In the course of that study it was also possible to conclude that at the household level a change in opinion in the area of CES affects in all periods with the same magnitude opinions in the other areas. It was confirmed by estimating the structural model with the imposed conditions of equal factor loadings. (original abstract)W artykule podjęta została problematyka zależności między odpowiedziami respondentów w ramach kwestionariusza badania kondycji gospodarstw domowych w Polsce. Wyróżnione zostały cztery obszary, w których respondenci udzielają odpowiedzi: bieżąca sytuacja gospodarstwa domowego (BSGD), bieżąca sytuacja gospodarki (BSG), prognozowana sytuacja gospodarstwa domowego (PSGD) i prognozowana sytuacja gospodarki (PSG). Dla każdego z obszarów z wykorzystaniem konfirmacyjnej analizy czynnikowej dla wielu grup dokonano estymacji modelu pomiarowego. Pokazano, że dla trzech z czterech obszarów (z wyjątkiem BSGD) możliwe jest wyselekcjonowanie pytań, które w spójny sposób będą mierzyły analizowany obszar. Dla obszaru BSGD wybrano zaś jedno pytanie wskaźnikowe opisujące ten obszar. W następnym kroku przeprowadzono estymację modelu strukturalnego, tym samym weryfikując związki między zmiennymi ukrytymi (obszarami). Wykazano, że odpowiedzi gospodarstw domowych na pytania dotyczące przyszłej sytuacji ich gospodarstwa domowego są powiązane z odpowiedziami udzielanymi w każdym z pozostałych trzech obszarów. Pokazano silne przełożenie między odpowiedziami dotyczącymi oceny bieżącej sytuacji gospodarczej i dotyczącymi prognozy przyszłej sytuacji gospodarczej oraz odpowiedziami dotyczącymi oceny bieżącej sytuacji gospodarczej i tymi, które dotyczą oceny bieżącej sytuacji gospodarstwa domowego. W toku prowadzonej analizy udało się również stwierdzić, że na poziomie gospodarstwa domowego (respondenta) zmiana opinii w obszarze oceny bieżącej sytuacji gospodarczej przekłada się w każdym momencie analizy na taką samą zmianę opinii w pozostałych obszarach, co związane było z możliwością estymacji modelu strukturalnego z narzuconymi warunkami równości ładunków czynnikowych. (abstrakt oryginalny