Ivan Mendieta-Muñoz

The literature on the empirical linkages between economic growth (or other measures of macroeconomic performance) and the functional distribution of income is copious on the short run. The sustained and simultaneous decline in average rates of real GDP growth and the labor share of income in the USA in recent decades has led to renewed interest in the long run, in light of the hypothesis of inequality-induced secular stagnation. This paper employs a vector error correction model with time-varying parameters and stochastic volatility to estimate the long-run interaction between real GDP growth, labor share, and the unemployment rate. Our key result indicates that a lower labor share is associated with a decline in the growth rate: economic growth is wage-led in the long run.

We study the time-varying effects of Tobin’s q and cash flow on investment dynamics in the USA using a vector autoregression model with drifting parameters and stochastic volatilities estimated via Bayesian methods. We find a significant variation over time of the response of investment to shocks in both variables. The time-varying sensitivity of investment to a shock in Tobin’s q (cash flow) decreased (increased) since the early 1960s through the early 1980s, increased (decreased) since the early 1980s through the early 2000s, and it has decreased (increased) importantly again since then. Thus, the time-varying response of investment to a shock to Tobin’s q has been almost the mirror image to the time-varying response of investment to a shock to cash flow. This implies that Tobin’s q and cash flow represent both complementary and alternative sources of information needed to understand short-run investment behavior.

Using a Bayesian threshold vector autoregression model for the US economy, this paper tests whether nonlinear dynamics can arise from the endogenous interactions between traditional business cycles, depicted by investment decisions, profitability levels and aggregate demand levels, and financial conditions, depicted by credit market conditions, thus considering that the latter are important sources of instability and possible nonlinear propagators of other shocks. The results support the characterization of nonlinear dynamics in the transmission of shocks since there is evidence of asymmetric responses of the variables across two different regimes of financial stress, responding more strongly during loose financial conditions.

This paper analyses US payroll share and components across states for the period 1977–2017. Findings include that spatial clustering in payroll shares decreased until the year 2000. States are clustered in low and high productivity groups. We relate this phenomenon to dualism. High labour productivity states featured high payroll shares early on, but now feature low payroll shares. We label this phenomenon decoupling of labour productivity from real wages. A Divisia Decomposition documents that Rust Belt states dominated the decline in US payroll share in the 1980s, whereas more recently large (coastal) states dominated. While we do not explain (potentially different) mechanisms, decoupling is apparent throughout.

We propose a structural representation of the correlated unobserved components model, which allows for a structural interpretation of the interactions between trend and cycle shocks. We show that point identification of the full contemporaneous matrix which governs the structural interaction between trends and cycles can be achieved via heteroskedasticity. We develop an efficient Bayesian estimation procedure that breaks the multivariate problem into a recursion of univariate ones. An empirical implementation for the US Phillips curve shows that our model is able to identify the magnitude and direction of spillovers of the trend and cycle components both within-series and between-series.