Empirical Essays on Monetary Policy and Transmission

This thesis presents four self-contained empirical research papers on monetary policy and monetary transmission using vector autoregression (VAR), structural VAR (SVAR), and Bayesian time-varying parameter VAR (TVP-VAR) models. The first two papers compare aspects of monetary policy and transmission in selected developed countries: Australia, the US, and the Euro area (Chapter 3); and Australia, the US, UK, and Canada (Chapter 4). The last two papers (Chapters 5 and 6) explore monetary policy and effects of monetary policy on inflation in Vietnam – a transition developing country. The empirical results indicate that the investment channel of monetary policy transmission plays a more important role than the consumption channel in Australia. Meanwhile the investment channel and the consumption channel make similar contributions to the overall transmission of monetary policy in the Euro area and the US. The difference between Australia and the Euro area appears to come from differences in housing investment responses, whereas Australia differs from the US mainly because it has a lower share of household consumption in total demand. Results from TVP-VAR models suggest that there were comovements in the monetary policy reactions to unemployment across countries before the recent Global Financial Crisis (GFC). The policy rate seems to react more strongly to unemployment changes in more recent years, especially in the US and UK. Monetary policy responses to inflation/deflation are observed to be divided into two groups, with the responses in the US and UK showing a different pattern to the responses in Canada and Australia. Monetary policy seems to react most aggressively against inflation/deflation in the US. The effects of monetary policy shocks on unemployment and inflation are similar across countries, and seem to have weakened over time. Results also suggest that monetary policy transmission to inflation in a transition country like Vietnam appears to work in a similar way to as in developed countries. The impulse response functions of inflation to shocks in monetary policy are plausible and robust across the VAR and SVAR models. The policy interest rate plays an important role in affecting inflation. For the case of Vietnam as a small, open economy, shocks to output and prices in trading partners also appear to have strong effects on domestic inflation. Allowing for the time-varying nature of the parameters and variance/covariance matrices, the results suggest that the State Bank of Vietnam (SBV) appears to have been steadily using monetary policy tools to contain inflation. TVP-VAR results also confirm that monetary policy in Vietnam appears to lead to reasonable inflation responses. The evidence therefore supports the argument that Vietnam’s monetary policy might be more effective than expected

Bank Credit, Trade Credit, and Profit: Evidence from Agricultural Firms in Vietnam

This paper investigates the relationships between bank credit and trade credit with profit of 130 agricultural firms listed on Vietnam’s stock exchanges in the period of 2008-2014. Using the GMM approach, the paper reveals inverted-U shaped (?) relationships between bank credit and trade credit with profit. Specifically, the optimal threshold of bank credit and trade credit to total assets of the firms are 0.4173 and 0.2425, respectively. The findings mean that if the ratio of bank credit to total assets exceeds the benchmark of 0.4173, firms should consider restructuring debts to get them back to the benchmark. To do so, firms should withdraw from those business fields that are not of profession, in addition to liquiditizing unused assets to repay debts and not using short-term credit to invest in long-term projects. Firms may use of trade credit wisely when other sources of finance are lacking. In concrete, firms can increase trade credit use if the ratio of trade credit to total assets is below 0.2425. Yet, if this ratio goes beyond this benchmark, firms should get its back to this benchmark, e.g., keeping a suitable amount of inventory

SkipFlow: Incorporating Neural Coherence Features for End-to-End Automatic Text Scoring

Deep learning has demonstrated tremendous potential for Automatic Text Scoring (ATS) tasks. In this paper, we describe a new neural architecture that enhances vanilla neural network models with auxiliary neural coherence features. Our new method proposes a new \textsc{SkipFlow} mechanism that models relationships between snapshots of the hidden representations of a long short-term memory (LSTM) network as it reads. Subsequently, the semantic relationships between multiple snapshots are used as auxiliary features for prediction. This has two main benefits. Firstly, essays are typically long sequences and therefore the memorization capability of the LSTM network may be insufficient. Implicit access to multiple snapshots can alleviate this problem by acting as a protection against vanishing gradients. The parameters of the \textsc{SkipFlow} mechanism also acts as an auxiliary memory. Secondly, modeling relationships between multiple positions allows our model to learn features that represent and approximate textual coherence. In our model, we call this \textit{neural coherence} features. Overall, we present a unified deep learning architecture that generates neural coherence features as it reads in an end-to-end fashion. Our approach demonstrates state-of-the-art performance on the benchmark ASAP dataset, outperforming not only feature engineering baselines but also other deep learning models.Comment: Accepted to AAAI 201

A dedicated state space for power system modeling and frequency and unbalance estimation

International audienceOver the last decades, a great deal of research has been focused on power quality issues in electrical energy transportation. We present a state-space representation to model dynamical power systems like electrical distribution systems. The proposed model is able to take into account all the dynamic behavior of a multiphase power system. It has been applied to model a typical three-phase power system and its unbalance, i.e., an electrical grid which can be perturbed by nonlinear loads and distributed renewable energy generation which is a typical changing system. Associated with an extended Kalman filter, the state-space model is used to iteratively estimate power quality parameters. Indeed, the symmetrical components of the power system, i.e., their amplitude and phase angle values, and the fundamental frequency can be calculated at each iteration without any prior knowledge. The proposed estimation technique is an evolving and adaptive method able to handle the changing power system. Its effectiveness has been evaluated by several tests. Results have been compared to other methods. They show the efficiency and better performance of the proposed method. The fundamental frequency and the symmetrical components are precisely estimated even under disturbed and time-varying conditions. This state-space representation can therefore be used in active power filtering schemes and in load frequency control strategies

MEASURING AND COMPENSATING FOR OFF-LINE TO RUNNING MACHINERY MOVEMENT

Actually, all rotating equipments which connected one to each other undergo a change in position during start-up (off-line) and this condition will affect the alignment of the shafts while running. The off-line to running movement characteristics of the vast majority of rotating machinery in industries have never been measured. It is very important to know how much movement occurred before concluding that it is insignificant and can be ignored. This paper will show the characteristics of both cold and hot misalignment. The purpose of this work is to analyze the influence of temperature to misalignment of rotating equipments that has been mentioned in some references but never been investigated. The objective of this work is to find out the characteristics of hot misalignment and to compensate for Off-Line to Running (OL2R) machinery movement. The results of the experiments and analysis show that the misalignment condition changes during operation and it strongly influences on the vibration level of the rotating machinery. In this case, the smaller the misalignment value, the smaller vibration level of the rotating machinery

A secure network coding based modify-and-forward scheme for cooperative wireless relay networks

This paper investigates the security at the physical layer of cooperative relay communications. Inspired by the principle of physical-layer network coding (PNC), we propose a new secure relaying scheme, namely secure PNC-based modify-and-forward (SPMF). In the proposed scheme, the relay node linearly combines the decoded data from the source node with an encrypted key before conveying the mixed data to the destination node. As both the linear PNC operation and encrypted key at the relay are unknown to the eavesdropper, the SPMF scheme provides a double security level in the system. Particularly, taking into account the practical scenario of the imperfect knowledge shared between the relay and destination, the secrecy outage probability (SOP) of the proposed SPMF scheme is analysed and evaluated in comparison with modify-and-forward, cooperative jamming, decode-and-forward and direct transmission schemes. The proposed scheme is shown to achieve a performance improvement of up to 3 dB when compared to the conventional schemes under imperfect knowledge of shared information between the nodes

Optimising energy efficiency of non-orthogonal multiple access for wireless backhaul in heterogeneous cloud radio access network

This paper studies the downlink problem of a cloud-based central station (CCS) to multiple base stations (BSs) in a heterogeneous cellular network sharing the same time and frequency resources. We adopt non-orthogonal multiple access (NOMA) and propose power allocation for the wireless downlink in the heterogeneous cloud radio access network (HCRAN). Taking into account practical channel modelling with power consumptions at BSs of different cell types (e.g. macro-cell, micro-cell, etc.) and backhauling power, we analyse the energy efficiency (EE) of the practical HCRAN utilising NOMA. Simulation results indicate that the proposed NOMA for the HCRAN outperforms the conventional orthogonal frequency division multiple access (OFDMA) scheme in terms of providing higher EE of up to four times. Interestingly, the results reveal a fact that the EE of the NOMA approach is not always an increasing function of the number of BSs but varies as a quasiconcave function. This motivates us to further introduce an optimisation problem to find the optimal number of BSs that maximises the EE of the HCRAN. It is shown that, with a low power supply at the CCS, a double number of micro BSs can be served by HCRAN providing an improved EE of up to 1.6 times compared to the macro BSs and RRHs, while they achieve the same EE performance with high-power CCS