Essays on Nonlinearities and Structural Breaks in the Relationships between Macroeconomic Variables

The dissertation is set out in three chapters, focusing on the structural changes that led to jobless recoveries in following the past three recessions, the asymmetric effects of fiscal stimulus over the business cycle, and the asymmetric effects of fiscal cuts and stimulus respectively. In the first chapter, I examine the three leading theoretical explanations for the recent jobless recoveries using a correlated unobserved components model of aggregate data for output, sales, employment, and hours. The main finding is that employment now respond to demand shocks in a way that is consistent with just-in-time utilization of labor resources. The second and the third chapter focus on asymmetric responses to fiscal policy. In the second chapter, I investigate the effects of government spending on U.S. economic activity using a threshold version of a structural vector autoregressive model. The empirical findings support state-dependent effects of fiscal policy. In particular, the effects of a government spending shock on output are significantly larger and more persistent when the economy has a high degree of underutilized resources than when the economy is close to capacity. The third chapter examines whether there are sign and size asymmetries in the responses of output, output components, and employment to fiscal policy. When the economy is not constrained, a large fiscal stimulus is more effective at increasing employment and output, and cuts have larger effects than increases

Sustainability of the Pension System in the Republic of Macedonia: Challenges and Solutions

The aim of the study is to create a forecasting model that will foresee the trend of the situation of the Pension, Insurance and Disability Fund of the Republic ofMacedonia. The methodology applied to evaluate the sustainability of pension system, and controlling the risk to pension funds, is forecast of all individual regressors through first order autoregressive model. This method will enable the assessment of the future uncertainty of the contributions and expenditures of pension insurance. The forecasted data show that in 2056, if no other reforms are undertaken, the increase in the percentage points of the number of employers is less than the increase in the number of pensioners for 3.9 percentage points. As per the natality and mortality, in the Republic of Macedonia natality will be only one third of its statistics in 2016, whereas mortality will double its value by 2056

Testing Stationarity with Unobserved Components Models

In the aftermath of the global financial crisis, competing measures of the trend in macroeconomic variables such as U.S. real GDP have featured prominently in policy debates. A key question is whether large shocks to macroeconomic variables will have permanent effects—i.e., in econometric terms, do the data contain stochastic trends? Unobserved-components models provide a convenient way to estimate stochastic trends for time series data, with their existence typically motivated by stationarity tests that allow at most a deterministic trend under the null hypothesis. However, given the small sample sizes available for most macroeconomic variables, standard Lagrange multiplier tests of stationarity will perform poorly when the data are highly persistent. To address this problem, we propose the use of a likelihood ratio test of stationarity based directly on the unobserved-components models used in estimation of stochastic trends. We demonstrate that a bootstrap version of this test has far better small-sample properties for empirically relevant data-generating processes than bootstrap versions of the standard Lagrange multiplier tests. An application to U.S. real GDP produces stronger support for the presence of large permanent shocks using the likelihood ratio test than using the standard tests

Fast and slow cancellations and trader behavior

We investigate how short-lived liquidity supply due to order cancellations affects the order-placement behavior of slow traders. When order cancellations increase, slow traders submit fewer and less aggressive orders. Both short- and long-lived liquidity supply have positive effects on the market overall, reducing spreads and increasing depth. We conclude that it is not necessary to require limit orders to have a minimum lifespan. We develop econometric and machine-learning frameworks that allow traders to predict whether a quote is likely to have a short or long life, increasing the ability of slow traders to respond strategically to changing order flow