Using a polynomial cointegration technique, this paper shows that the bilateral US current account balance with China has a U-shaped relationship with the life expectancy gap between the US and China. A narrowing gap initially increases the US deficit with China, but eventually, this increased US deficit falls with the further catching-up of Chinese life expectancy. The life expectancy gap between the two countries has been below the threshold level since 2013, and this demographic trend has the potential to improve the US deficit with China. This U-shaped relationship can be theoretically reproduced. A two-country overlapping generations model indicates that the effect of life expectancy is decomposed into four components: retirement savings, social security burden, the number of elderly workers, and the productivity of elderly workers. The total effect of foreign life expectancy on the home current account balance exhibits a sign change in the catching-up of foreign life expectancy.

This paper assesses the role of political tensions between the USA and China and global market forces in explaining oil price fluctuations. To this end, we take part of the previous literature, which highlights (i) the importance of political events in explaining oil price dynamics, (ii) time-varying patterns in the oil market, and (iii) asymmetries in the impact of political tensions and uncertainty on oil prices. While this literature generally focuses on one of these features, we account for all of them simultaneously, allowing for a complete and meaningful investigation of political tensions on oil prices. To this end, we rely on quantile autoregressive distributed lag error-correction models, which are specifically designed to address both the long-run and short-run dynamics across a range of quantiles in a fully parametric setting. Our results show evidence of a quantile-dependent long-term relationship between oil prices and their determinants over the 1958–2022 period, which is also time varying across quantiles: the adjustment speed toward the long-term equilibrium is faster for the highest quantiles, fluctuating between 4% and 6% in the recent period. Overall, our findings highlight the increased role played by China in the oil market since the mid-2000s.

Causal flow analyses combined with time series analyses are used to examine price relationships among fresh broiler retail markets (Northeast, South, Midwest, and West). Results indicate structural changes have occurred in this industry. Reasons for changes in price relationships include the perishable nature of fresh broilers, along with vertical integration and increases in production and concentration in the industry. The four markets are integrated, but the level of integration has decreased over time. With the markets becoming more exogenous, there may be a decrease in society’s welfare. The South market is the most important market for price discovery.

In recent decades, the labour share has experienced a downward trend in Portugal at the same time as a weaker and anaemic growth pattern. This seems to suggest that the fall in the labour share represents an important constraint on Portuguese economic growth, which is contrary to the orthodox claims around wage restraint policies – namely, that such policies are a necessary condition of improved macroeconomic performance, owing to their positive effects on private investment through higher profits and on net exports through reduced unit labour costs and a corresponding rise in competitiveness. This study assesses the relationship between labour share growth and economic growth by performing a time series econometric analysis focused on Portugal from 1971 to 2021. Findings show that labour share growth has positively impacted on economic growth in Portugal, which is in line with heterodox claims and particularly with post-Keynesian economics on the beneficial effects on private consumption played by the growth of wages. Findings also confirm that the Portuguese economy has followed a wage-led growth regime instead of a profit-led growth regime; that is, a rise in wages increases aggregate demand and, therefore, boosts economic growth because its beneficial effect on private consumption more than compensates for a prejudicial effect on private investment and on net exports. The study points out the urgent need to adopt public policies to support the growth of wages to avoid more decades of dismal growth and a new ‘secular stagnation’ in Portugal.

This article analyses from a Keynesian approach the effect of wage devaluation on the Spanish labour market during the Great Recession post-2008. It challenges the pro-flexibility literature, which attributes to labour relations reforms the prevention of larger job destruction in the recession and a larger reduction in unemployment during the subsequent expansion. Instead, we examine the role of wage devaluation in the operation of Okun’s law and gross domestic product, using an extended version of the Bhaduri–Marglin model. We find that wage devaluation has not significantly modified Okun’s law and that through its impact on income distribution, the unemployment rate rose by 1.9 percentage points. We therefore provide evidence for the negative effect of wage devaluation on gross domestic product and the positive effect on the unemployment rate.

Simple ordinary least squares estimates indicate that absent fathers boost probabilities of adolescent criminal behavior by 16–38%, but those numbers likely are biased by unobserved heterogeneity. This paper first presents an economic model explaining that unobserved heterogeneity. Then turning to empirics, fixed effects, which attempt to address that bias, suggest that absent fathers reduce certain types of adolescent crime, while lagged-dependent variable models suggest the opposite. Those conflicting conclusions are resolved by an approach that combines those two estimators using an orthogonal reparameterization approach, with model parameters calculated using a Bayesian algorithm. The main finding is that absent fathers do not appear to directly affect adolescent criminal activity. Rather, families with absent fathers possess traits that appear to correlate with increased adolescent criminal behaviors.

When studying the Federal Open Market Committee’s (FOMC’s) interest rate rule, some authors, such as Gonzalez-Astudillo [(2018) Journal of Monetary, Credit, and Banking 50(1), 115–154.], find evidence for changes in inflation and output gap responses. Others, such as Sims and Zha [(2006) American Economic Review 96(1), 54–81.], only find evidence for a change in the variance of the interest rate rule. In this paper, I develop a new two-regime Markov-switching model that probabilistically performs variable selection and identification of parameter change for each variable in the model. I find substantial evidence that there have been changes in the FOMC’s response to the unemployment gap and in the volatility of the rule. When the FOMC responds strongly to the unemployment gap, I find a bimodal density for the inflation response coefficient. Despite the bimodal density, there is a low probability that there have been changes in the FOMC’s response to inflation.

This article shows how new time series models can be used to track the progress of an epidemic, forecast key variables and evaluate the effects of policies. The univariate framework of Harvey and Kattuman (2020, Harvard Data Science Review, Special Issue 1—COVID-19, https://hdsr.mitpress.mit.edu/pub/ozgjx0yn) is extended to model the relationship between two or more series and the role of common trends is discussed. Data on daily deaths from COVID-19 in Italy and the UK provides an example of leading indicators when there is a balanced growth. When growth is not balanced, the model can be extended by including a non-stationary component in one of the series. The viability of this model is investigated by examining the relationship between new cases and deaths in the Florida second wave of summer 2020. The balanced growth framework is then used as the basis for policy evaluation by showing how some variables can serve as control groups for a target variable. This approach is used to investigate the consequences of Sweden’s soft lockdown coronavirus policy in the spring of 2020.

The Covid-19 pandemic has put forecasting under the spotlight, pitting epidemiological models against extrapolative time-series devices. We have been producing real-time short-term forecasts of confirmed cases and deaths using robust statistical models since 20 March 2020. The forecasts are adaptive to abrupt structural change, a major feature of the pandemic data due to data measurement errors, definitional and testing changes, policy interventions, technological advances and rapidly changing trends. The pandemic has also led to abrupt structural change in macroeconomic outcomes. Using the same methods, we forecast aggregate UK unemployment over the pandemic. The forecasts rapidly adapt to the employment policies implemented when the UK entered the first lockdown. The difference between our statistical and theory based forecasts provides a measure of the effect of furlough policies on stabilising unemployment, establishing useful scenarios had furlough policies not been implemented.

A new class of time series models is used to track the progress of the COVID-19 epidemic in the UK in early 2021. Models are fitted to England and the regions, as well as to the UK as a whole. The growth rate of the daily number of cases and the instantaneous reproduction number are computed regularly and compared with those produced by SAGE. The results from figures published each day are compared with results based on figures by specimen date, which may be more accurate but are subject to substantial revisions. It is then shown how data from the two different sources can be combined in bivariate models.

Target date funds (TDFs) are becoming increasingly popular investment choices among investors with long-term prospects. Examples include members of superannuation funds seeking to save for retirement at a given age. TDFs provide efficient risk exposures to a diversified range of asset classes that dynamically match the risk profile of the investment payoff as the investors age. This is often achieved by making increasingly conservative asset allocations over time as the retirement date approaches. Such dynamically evolving allocation strategies for TDFs are often referred to as glide paths. We propose a systematic approach to the design of optimal TDF glide paths implied by retirement dates and risk preferences and construct the corresponding dynamic asset allocation strategy that delivers the optimal payoffs at minimal costs. The TDF strategies we propose are dynamic portfolios consisting of units of the growth-optimal portfolio (GP) and the risk-free asset. Here, the GP is often approximated by a well-diversified index of multiple risky assets. We backtest the TDF strategies with the historical returns of the S&P500 total return index serving as the GP approximation.

The paper solves the loss reserving problem using Kalman recursions in linear statespace models. In particular, if one orders claims data from run-off triangles to time series with missing observations, then state space formulation can be applied for projections or interpolations of IBNR (Incurred But Not Reported) reserves. Namely, outputs of the corresponding Kalman recursion algorithms for missing or future observations can be taken as the IBNR projections. In particular, by means of such recursive procedures one can perform effectively simulations in order to estimate numerically the distribution of IBNR claims which may be very useful in terms of setting and/or monitoring of prudency level of loss reserves. Moreover, one can generalize this approach to the multivariate case of several dependent run-off triangles for correlated business lines and the outliers in claims data can be also treated effectively in this way. Results of a numerical study for several sets of claims data (univariate and multivariate ones) are presented.

We investigate economic resilience of UK regions before, during and after the 2007/8 global financial crisis. We date business cycle turning points in real output, employment and productivity to assess the resilience dimensions of resistance, recovery and renewal and rank the economic resilience of regions in a resilience scorecard. Our empirical results reveal that the business cycle in productivity has not returned to its pre-recession peak level for Yorkshire and the Humber and the employment level has not recovered in Scotland. The resilience scorecard ranks the South East as the most resilient region with Northern Ireland the least resilient.

We estimate trend UK labour productivity growth using a Hodrick-Prescott filter method. We use the results to compare downturns where the economy fell below its pre-existing trend. We find that the current productivity slowdown has resulted in productivity being 19.7 per cent below the pre-2008 trend path in 2018. This is nearly double the previous worst productivity shortfall ten years after the start of a downturn. On this criterion the slowdown is unprecedented in the past 250 years. We conjecture that this reflects a combination of adverse circumstances, namely, a financial crisis, a weakening impact of ICT and impending Brexit.

We use linear time series and wavelets approach to study the relationships between U.S. and international prices for corn, soybeans, and cotton. We then compare results obtained with each approach and verify that structural breaks discovered with wavelet analysis match those produced with subsequent partial-period cointegration analysis. We find little evidence that short-term fluctuations between domestic and international prices are stable, while long-term relationships for many price pairs experience distinct structural breaks. We further find that even though China is among the largest importers of U.S. agricultural products, its commodity prices share little or no relationship with those prevailing in U.S. markets.

Cattle are costly to transport, which could lead to segmented regional cattle markets. The cointegration of cattle prices over regions has been of research interest for decades. This article investigates price cointegration between regional cattle markets in the United States and proposes a simple procedure for incorporating a flexible transition function into an economic indicator–controlled smooth transition autoregressive (ECON-STAR) model to evaluate market dynamics. The empirical results show that these markets have been highly integrated when excess supply exists, but when cattle inventories decrease, the market pattern becomes very regionally segmented.

As a benchmark mortality model in forecasting future mortality rates and hedging longevity risk, the widely employed Lee–Carter model (Lee, R.D. and Carter, L.R. (1992) Modeling and forecasting U.S. mortality. Journal of the American Statistical Association, 87, 659–671.) suffers from a restrictive constraint on the unobserved mortality index for ensuring model’s identification and a possible inconsistent inference. Recently, a modified Lee–Carter model (Liu, Q., Ling, C. and Peng, L. (2018) Statistical inference for Lee–Carter mortality model and corresponding forecasts. North American Actuarial Journal, to appear.) removes this constraint and a simple least squares estimation is consistent with a normal limit when the mortality index follows from a unit root or near unit root AR(1) model with a nonzero intercept. This paper proposes a bias-corrected estimator for this modified Lee–Carter model, which is consistent and has a normal limit regardless of the mortality index being a stationary or near unit root or unit root AR(1) process with a nonzero intercept. Applications to the US mortality rates and a simulation study are provided as well.

This article uses historical US inflation data covering over two centuries to examine the impact of the establishment of the US Federal Reserve on average US inflation and inflation uncertainty. We find that the founding of the Fed is associated with higher average US inflation and lower inflation uncertainty. Critically, these results are not driven by the post-1980 period, where the Fed policy is characterised by the dual mandate. Other important results are that the gold standard period is associated with both lower inflation and inflation uncertainty, and that banking and stock market crises are a positive determinant of inflation uncertainty and perhaps inflation. World Wars I and II and the US Civil War are associated with both higher inflation and higher inflation uncertainty. In addition, we find that the central bank has responded to increasing inflation uncertainty in a stabilising manner in support of the Holland hypothesis.

In this paper we seek to characterize the robustness of the ENSO/soybean price relationship and to determine whether it has practical economic content. If such a meaningful relationship exists, the implications could be profound for commodity traders and for public sector investments in climate forecasting capabilities. Also, the validity of economic evaluations of climate impacts and climate forecasts based on ENSO-price independence would come into question. Our findings suggest a relationship between interannual climate and soybean prices, although we are not able to attribute the relationship to ENSO or to say that ENSO is economically important.

The peseta was the Spanish currency for more than a century and, during this time, it played a remarkable role in adjusting the balance of payments. This paper presents a chronology of the moments when the adjustment was crucial, which, consistent with the macro-trilemma, coincided with periods of external openness. Moreover, this paper provides empirical support to the thesis that links the exceptionality of a floating peseta during the gold standard with fiscal profligacy.