Gastric motility: Measurement, symptoms and therapy

Gastric motility disorders, including delayed gastric emptying (gastroparesis), impaired postprandial fundic relaxation, and gastric myoelectrical disorders, can occur in type 1 diabetes, chronic renal failure, and functional dyspepsia (FD). Symptoms like upper abdominal pain, early satiation, bloating, nausea and vomiting may be related to gastroparesis. Diabetic gastroparesis is related to autonomic neuropathy. Scintigraphy is the gold standard in measuring gastric emptying, but it is expensive, requires specific equipment, and exposes patients to radiation. It also gives information about the intragastric distribution of the test meal. The 13C-octanoic acid breath test (OBT) is an alternative, indirect method of measuring gastric emptying with a stable isotope. Electrogastrography (EGG) registers the slow wave originating in the pacemaker area of the stomach and regulating the peristaltic contractions of the antrum. This study compares these three methods of measuring gastric motility in patients with type 1 diabetes, functional dyspepsia, and chronic renal failure. Currently no effective drugs for treating gastric motility disorders are available. We studied the effect of nizatidine on gastric emptying, because in preliminary studies this drug has proven to have a prokinetic effect due to its cholinergic properties. Of the type 1 patients, 26% had delayed gastric emptying of solids as measured by scintigraphy. Abnormal intragastric distribution of the test meal occurred in 37% of the patients, indicating impaired fundic relaxation. The autonomic neuropathy score correlated positively with the gastric emptying rate of solids (P = 0.006), but HbA1C, plasma glucose levels, or abdominal symptoms were unrelated to gastric emptying or intragastric distribution of the test meal. Gastric emptying of both solids and liquids was normal in all FD patients but abnormal intragastric distribution occurred in 38% of the patients. Nizatidine improved symptom scores and quality of life in FD patients, but not significantly. Instead of enhancing, nizatidine slowed gastric emptying in FD patients (P < 0.05). No significant difference appeared in the frequency of the gastric slow waves measured by EGG in the patients and controls. The correlation between gastric half-emptying times of solids measured by scintigraphy and OBT was poor both in type 1 diabetes and FD patients. According to this study, dynamic dual-tracer scintigraphy is more accurate than OBT or EGG in measuring gastric emptying of solids. Additionally it provides information about gastric emptying of liquids and the intragastric distribution of the ingested test meal.

Bootstrapping the Error Correction Model Cointegration Test

This paper is concerned with using the bootstrap to obtain improved critical values for the error correction model (ECM) cointegration test in dynamic models. In the paper we investigate the effects of dynamic specification on the size and power of the ECM cointegration test with bootstrap critical values. The results from a Monte Carlo study show that the size of the bootstrap ECM cointegration test is close to the nominal significance level. We find that overspecification of the lag length results in a loss of power. Underspecification of the lag length results in size distortion. The performance of the bootstrap ECM cointegration test deteriorates if the correct lag length is not used in the ECM. The bootstrap ECM cointegration test is therefore not robust to model misspecification.

Dynamic Factor Models and Forecasting Finnish Macroeconomic Variables

In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).